19 PRICE INDICES USING AN ARTIFICIAL DATA SET
Author:
International Monetary Fund
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Language:
English
Print Publication Date:
25 Aug 2004
Keywords:
M&G; quantity vector; price relative; index number formula; Lowe index; reference period; Price indexes; Export fluctuations
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Abstract

19.1 In order to give the reader some idea of how much the various index numbers might differ using a “real” data set, virtually all the major indices defined in the previous chapters are computed in this chapter using an artificial data set consisting of prices and quantities for six commodities over five periods. The data are described in paragraphs 19.3 and 19.4.

Introduction

19.1 In order to give the reader some idea of how much the various index numbers might differ using a “real” data set, virtually all the major indices defined in the previous chapters are computed in this chapter using an artificial data set consisting of prices and quantities for six commodities over five periods. The data are described in paragraphs 19.3 and 19.4.

19.2 The contents of the remaining sections are outlined in this paragraph. In the section starting with paragraph 19.5, two of the early unweighted indices are computed: the Carli and Jevons indices. Two of the earliest weighted indices are also computed in this section: the Laspeyres and Paasche indices. Both fixed base and chained indices are computed. In the section starting with paragraph 19.9, various asymmetrically1 weighted indices are computed. In the section starting with paragraph 19.17, symmetrically2 weighted indices are computed. Some of these indices are superlative, while others are not. The section starting with paragraph 19.23 computes some superlative indices using two stages of aggregation and compares the resulting two-stage indices with their single-stage counterparts. The following section computes various Lloyd-Moulton indices3 and compares them with superlative indices. The section starting with paragraph 19.32 computes two additive percentage change decompositions for the Fisher ideal index and compares the resulting decompositions, which are found to be very similar. Up to this point, all the indices that are computed are weighted or unweighted bilateral price indices; i.e., the index number formula depends only on the price and quantity data pertaining to the two periods whose prices are being compared. In the final three sections of this chapter, various indices involving the data pertaining to three or more periods are computed. In the section starting with paragraph 19.37, Lowe and Young indices are computed where the data of period 1 are used as quantity or share weights in conjunction with the price data of periods 3 to 5, so that the weight reference period is 1 and the price reference period is 3. In the final two sections, various mid-year indices are computed that are based on the Lowe and Young formulae. Recall that for these two index number formulae, the price reference period does not coincide with the weight reference period. Thus these indices are not bilateral index number formulae.

The artificial data set

19.3 The period can be thought of as somewhere between a year and five years. The trends in the data are generally more pronounced than would be seen in the course of a year. The price and quantity data are listed in Tables 19.1 and 19.2. For convenience, the period t nominal expenditures, ptqt≡Σi=1npitqit are listed along with the corresponding period t expenditure shares, sit≡pitqit/ptqt in Table 19.3.

19.4 The trends that were built into Tables 19.1 to 19.3 are now explained in this paragraph. Think of the first four commodities as the consumption of various classes of goods in some economy, while the last two commodities are the consumption of two classes of services. Think of the first good as agricultural consumption; its quantity fluctuates around 1 and its price also fluctuates around 1.4 The second good is energy consumption; its quantity shows a gently upward trend during the five periods with some minor fluctuations. Note, however, that the price of energy fluctuates wildly from period to period.5 The third good is traditional manufactures. Rather high rates of price inflation are assumed for this commodity for periods 2 and 3 which diminish to a very low inflation rate by the end of the sample period.6 The consumption of traditional manufactured goods is more or less static in the data set. The fourth commodity is high-technology manufactured goods, for example computers, video cameras and compact disks. The demand for these high-technology commodities grows 12 times over the sample period, while the final period price is only one-tenth of the first period price. The fifth commodity is traditional services. The price trends for this commodity are similar to those of traditional manufactures, except that the period-to-period inflation rates are a little higher. The demand for traditional services, however, grows much more strongly than for traditional manufactures. The final commodity is high-technology services, for example telecommunications, wireless phones, Internet services and stock market trading. For this final commodity, the price shows a very strong downward trend to end up at 20 per cent of the starting level, while demand increases fivefold. The movements of prices and quantities in this artificial data set are more pronounced than the year-to-year movements that would be encountered in a typical country, but they do illustrate the problem facing compilers of the consumer price index (CPI); namely, year-to-year price and quantity movements are far from being proportional across commodities, so the choice of index number formula will matter.

Table 19.1

Prices for six commodities

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Table 19.2

Quantities for six commodities

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table 19.3

Expenditures and expenditure shares for six commodities

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Early price indices: The Carli, Jevons, Laspeyres and Paasche indices

19.5 Every price statistician is familiar with the Laspeyres index PL defined by equation (15.5) and the Paasche index Pp defined by equation (15.6) in Chapter 15. These indices are listed in Table 19.4 along with two unweighted indices that were considered in previous chapters: the Carli index defined by equation (16.45) and the Jevons index defined by equation (16.47) in Chapter 16, The indices in Table 19.4 compare the prices in period t with the prices in period 1, that is, they are fixed base indices. Thus the period t entry for the Carli index, PC, is simply the arithmetic mean of the six price relatives, Σi=16(1/6)(pit/pi1) while the period t entry for the Jevons index, PJ, is the geometric mean of the six price relatives, Πi=16(pit/pi1)1/6.

19.6 Note that by period 5, the spread between the fixed base Laspeyres and Paasche price indices is enormous: PL is equal to 1.4400 while Pp is 0.7968, a spread of 81 per cent. Since both these indices have exactly the same theoretical justification, it can be seen that the choice of index number formula matters a lot. The period 5 entry for the Carli index, 0.9833, falls between the corresponding Paasche and Laspeyres indices but the period 5 Jevons index, 0.6324, does not. Note that the Jevons index is always considerably below the corresponding Carli index. This will always be the case (unless prices are proportional in the two periods under consideration) because a geometric mean is always equal to or less than the corresponding arithmetic mean.7

19.7 It is of interest to recalculate the four indices listed in Table 19.4 using the chain principle rather than the fixed base principle. The expectation is that the spread between the Paasche and Laspeyres indices will be reduced by using the chain principle. These chain indices are listed in Table 19.5.

19.8 It can be seen comparing Tables 19.4 and 19.5 that chaining eliminated about two-thirds of the spread between the Paasche and Laspeyres indices. Nevertheless, even the chained Paasche and Laspeyres indices differ by about 18 per cent in period 5, so the choice of index number formula still matters. Note that chaining did not affect the Jevons index. This is an advantage of the index but the lack of weighting is a fatal flaw.8 Using the economic approach to index number theory, there is an expectation that the “truth” lies between the Paasche and Laspeyres indices. From Table 19.5, it can be seen that the unweighted Jevons index is far below this acceptable range. Note that chaining did not affect the Carli index in a systematic way for the artificial data set: in periods 3 and 4, the chained Carli is above the corresponding fixed base Carli; but in period 5, the chained Carli is below the fixed base Carli.9

Asymmetrically weighted price indices

19.9 This section contains a systematic comparison of all of the asymmetrically weighted price indices (with the exception of the Lloyd-Moulton index, which will be considered later). The fixed base indices are listed in Table 19.6. The fixed base Laspeyres and Paasche indices, PL and PP, are the same as those indices listed in Table 19.4. The Palgrave index, PPAL, is defined by equation (16.55). The indices denoted by PGL and PGP are the geometric Laspeyres and geometric Paasche indices,10 which are special cases of the class of geometric indices defined by Konüs and Byushgens (1926); see equation (15.78). For the geometric Laspeyres index, PGL, the exponent weight αi for the i th price relative is si1 where si1 is the base period expenditure share for commodity i. The resulting index should be considered an alternative to the fixed base Laspeyres index, since both of these indices make use of the same information set. For the geometric Paasche index, PGP, the exponent weight for the i th price relative is sit, where sit is the current period expenditure shares. Finally, the index PHL is the harmonic Laspeyres index that was defined by equation (16.59).

Table 19.4

The fixed base Laspeyres, Paasche, Carli and Jevons indices

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Table 19.5

Chain Laspeyres, Paasche, Carli and Jevons indices

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Table 19.6

Asymmetrically weighted fixed base indices

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Table 19.7

Asymmetrically weighted fixed base indices

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19.10 By looking at the period 5 entries in Table 19.6, it can be seen that the spread between all these fixed base asymmetrically weighted indices has increased to be even larger than the earlier spread of 81 per cent between the fixed base Paasche and Laspeyres indices. In Table 19.6, the period 5 Palgrave index is about three times as big as the period 5 harmonic Laspeyres index, PHL. Again, this illustrates the point that because of the non-proportional growth of prices and quantities in most economies today, the choice of index number formula is very important.

19.11 It is possible to explain why certain of the indices in Table 19.6 are bigger than others. It can be shown that a weighted arithmetic mean of n numbers is equal to or greater than the corresponding weighted geometric mean of the same n numbers, which in turn is equal to or greater than the corresponding weighted harmonic mean of the same n numbers.12 It can be seen that the three indices PPAL, PGP and PP all use the current period expenditure shares, sit to weight the price relatives (pit/pi1), but PPAL is a weighted arithmetic mean of these price relatives, PGP is a weighted geometric mean of these price relatives and PP is a weighted harmonic mean of these price relatives. Thus by Schlömilch’s inequality, it must be the case that:12

P P A L ≥ P G P ≥ P P ( 19.1 )

19.12 Table 19.6 shows that the inequalities (19.1) hold for each period. It can also be verified that the three indices PL, PGL and PHL all use the base period expenditure shares si1 to weight the price relatives (pit/pi1), but PL is a weighted arithmetic mean of these price relatives, PGL is a weighted geometric mean of these price relatives, and PHL is a weighted harmonic mean of these price relatives. Thus by Schlömilch’s inequality, it must be the case that:13

P L ≥ P G L ≥ P H L ( 19.2 )

Table 19.6 shows that the inequalities (19.2) hold for each period.

19.13 All the asymmetrically weighted price indices are compared using the chain principle and are listed in Table 19.7.

19.14 Table 19.7 shows that although the use of the chain principle dramatically reduced the spread between the Paasche and Laspeyres indices PP and PL compared to the corresponding fixed base entries in Table 19.6, the spread between the highest and lowest asymmetrically weighted indices in period 5 (the Palgrave index PPAL and the harmonic Laspeyres index PHL) does not fall as much: the fixed base spread is 1.6720/0.5556 = 3.01, while the corresponding chain spread is 1.7893/0.7299 = 2.45. Thus, in this particular case, the use of the chain principle combined with the use of an index number formula that uses the weights of only one of the two periods being compared did not lead to a significant narrowing of the huge differences that these formulae generated using the fixed base principle. With respect to the Paasche and Laspeyres formulae, however, chaining did significantly reduce the spread between these two indices.

19.15 Is there an explanation for the results reported in the previous paragraph? It can be shown that all six of the indices that are found in the inequalities (19.1) and (19.2) approximate each other to the first order around an equal prices and quantities point. Thus with smooth trends in the data, it is expected that all the chain indices will more closely approximate each other than the fixed base indices because the changes in the individual prices and quantities are smaller using the chain principle. This expectation is realized in the case of the Paasche and Laspeyres indices, but not with the others. For some of the commodities in the data set, however, the trends in the prices and quantities are not smooth. In particular, the prices for the first two commodities (agricultural products and oil) bounce up and down. As noted by Szulc (1983), this will tend to cause the chain indices to have a wider dispersion than their fixed base counterparts. In order to determine if it is the bouncing prices problem that is causing some of the chained indices in Table 19.7 to diverge from their fixed base counterparts, all the indices in Tables 19.6 and 19.7 were computed again but excluding commodities 1 and 2 from the computations. The results of excluding these bouncing commodities may be found in Tables 19.8 and 19.9.

19.16 It can be seen that excluding the bouncing price commodities does cause the chain indices to have a much narrower spread than their fixed base counterparts. Thus, the conclusion is that if the underlying price and quantity data are subject to reasonably smooth trends over time, then the use of chain indices will narrow considerably the dispersion in the asymmetrically weighted indices. In the next section, index number formulae that use weights from both periods in a symmetric or even-handed manner are computed.

Table 19.8

Asymmetrically weighted fixed base indices for commodities 3–6

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Table 19.9

Asymmetrically weighted chained indices for commodities 3–6

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Symmetrically weighted indices: Superlative and other indices

19.17 Symmetrically weighted indices can be decomposed into two classes: superlative indices and other symmetrically weighted indices. Superlative indices have a close connection to economic theory. As was seen in paragraphs 17.27 to 17.49 of Chapter 17, a superlative index is exact for a representation of the consumer’s preference function or the dual unit cost function that can provide a second-order approximation to arbitrary (homothetic) preferences. Four important superlative indices were considered in previous chapters:

19.18 These four symmetrically weighted superlative price indices are listed in Table 19.10 using the fixed base principle. Also listed in Table 19.10 are two symmetrically weighted (but not superlative) price indices:14

  • the Marshall-Edgeworth price index PME, defined in paragraph 15.18;

  • the Drobisch price index PD, defined by equation (15.12).

19.19 Note that the Drobisch index PD is always equal to or greater than the corresponding Fisher index PF. This follows from the fact that the Fisher index is the geometric mean of the Paasche and Laspeyres indices, while the Drobisch index is the arithmetic mean of the Paasche and Laspeyres indices, and an arithmetic mean is always equal to or greater than the corresponding geometric mean. Comparing the fixed base asymmetrically weighted indices in Table 19.6 with the symmetrically weighted indices in Table 19.10, it can be seen that the spread between the lowest and highest index in period 5 is much less for the symmetrically weighted indices. The spread is 1.6720/0.5556 = 3.01 for the asymmetrically weighted indices, but only 1.2477/ 0.9801 = 1.27 for the symmetrically weighted indices. If the comparisons are restricted to the superlative indices listed for period 5 in Table 19.10, then this spread is further reduced to 1.2477/1.0712= 1.16; i.e., the spread between the fixed base superlative indices is “only” 16 per cent compared to the fixed base spread between the Paasche and Laspeyres indices of 81 per cent (1.4400/ 0.7968 = 1.81). There is an expectation that the spread between the superlative indices will be further reduced by using the chain principle.

Table 19.10

Symmetrically weighted fixed base indices

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Table 19.11

Symmetrically weighted indices using the chain principle

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19.20The symmetrically weighted indices are computed using the chain principle. The results may be found in Table 19.11.

19.21 A quick glance at Table 19.11 shows that the combined effect of using both the chain principle as well as symmetrically weighted indices is to dramatically reduce the spread between all indices constructed using these two principles. The spread between all the symmetrically weighted indices in period 5 is only 1.2333/1.2155 = 1.015 or 1.5 per cent and the spread between the four superlative indices in period 5 is an even smaller 1.2333/ 1.2224= 1.009, or about 0.1 per cent. The spread in period 5 between the two most commonly used superlative indices, the Fisher PF and the Törnqvist PT is truly tiny: 1.2226/1.2224 = 0.0002.15

19.22 The results listed in Table 19.11 reinforce the numerical results tabled by Hill (2002) and Diewert (1978, p. 894); the most commonly used chained superlative indices will generally give approximately the same numerical results.16 In particular, the chained Fisher, Törnqvist and Walsh indices will generally approximate each other very closely.

Superlative indices constructed in two stages of aggregation

19.23 Attention is now directed to the differences between superlative indices and their counterparts that are constructed in two stages of aggregation; see paragraphs 17.55 to 17.60 of Chapter 17 for a discussion of the issues and a listing of the formulae used. Using the artificial data set, the first four commodities are combined into a goods aggregate and the last two commodities into a services aggregate. In the second stage of aggregation, the goods and services components will be aggregated into an all-items index.

19.24 The results for the two-stage aggregation procedure using period 1 as the fixed base for the Fisher index PF, the Törnqvist index PT and the Walsh and implicit Walsh indexes, PW and PIW, are reported in Table 19.12.

19.25 Table 19.12 shows that the fixed base single stage superlative indices generally approximate their fixed base two-stage counterparts fairly closely, with the exception of the Fisher formula. The divergence between the single-stage Fisher index PF and its two-stage counterpart PF2S in period 5 is 1.1286/1.0712 = 1.05 or 5 per cent. The other divergences are 2 per cent or less.

19.26 Using chain indices, the results of the two-stage aggregation procedure are reported in Table 19.13. Again, the single-stage and their two-stage counterparts are listed for the Fisher index PF, the Törnqvist index PT and the Walsh and implicit Walsh indexes, PW and PIW.

19.27 Table 19.13 shows that the chained single-stage superlative indices generally approximate their fixed base two-stage counterparts very closely indeed. The divergence between the chained single-stage Törnqvist index PT and its two-stage counterpart PT2s in period 5 is 1.2300/1.2224= 1.006 or 0.6 per cent. The other divergences are all less than this. Given the large dispersion in period-to-period price movements, these two-stage aggregation errors are not large.

Lloyd-Moulton price indices

19.28 The next formula that will be illustrated using the artificial data set is the Lloyd (1975) and Moulton (1996) index PLM, defined by equation (17.71). Recall that this formula requires an estimate for the parameter σ, the elasticity of substitution between all commodities being aggregated. Recall also that if σ equals 0, then the Lloyd-Moulton index collapses down to the ordinary Laspeyres index, PL. When σ equals 1, the Lloyd-Moulton index is not defined, but it can be shown that the limit of PLMσ as σ approaches t is PGL, the geometric Laspeyres index or the logarithmic Laspeyres index with base period shares as weights. This index uses the same basic information as the fixed base Laspeyres index PL, and so it is a possible alternative index for CPI compilers to use. As was shown by Shapiro and Wilcox (1997a),17 the Lloyd-Moulton index may be used to approximate a superlative index using the same information that is used in the construction of a fixed base Laspeyres index, provided that an estimate for the parameter σ is available. This methodology will be tested using the artificial data set. The superlative index that is to be approximated is the chain Fisher index18 (which approximates the other chained superlative indices listed in Table 19.11 very closely). The chained Fisher index PF is listed in column 2 of Table 19.14 along with the fixed base Lloyd-Moulton indices PLMσ for σ equal to 0 (this reduces to the fixed base Laspeyres index PL), 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 and 1 (which is the fixed base geometric index PGL). Note that the Lloyd-Moulton indices steadily decrease as the elasticity of substitution σ is increased.19

Table 19.12

Fixed base superlative single-stage and two-stage indices

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Table 19.13

Chained superlative single-stage and two-stage indices

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Table 19.14

Chained Fisher and fixed base Lloyd-Moulton indices

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19.29 Table 19.14 shows that no single choice of the elasticity of substitution σ will lead to a Lloyd-Moulton price index PLMσ that will closely approximate the chained Fisher index PF for periods 2, 3, 4 and 5. To approximate PF in period 2, it is necessary to choose σ close to 0.1; to approximate PF in period 3, choose c close to 0.3; to approximate PF in period 4, choose σ between 0.4 and 0.5; and to approximate PF in period 5, choose a between 0.7 and 0.8.20

19.30 The computations for the Lloyd-Moulton indices listed in Table 19.14 are now repeated except that the chain principle is used to construct the Lloyd-Moulton indices; see Table 19.15. Again, the object is to approximate the chained Fisher price index PF which is listed as the second column in Table 19.15. In Table 19.15, PLM0 is the chained Laspeyres index and PLM1 is the chained geometric Laspeyres or geometric index using the expenditure shares of the previous period as weights.

19.31 Table 19.15 shows that again no single choice of the elasticity of substitution σ will lead to a Lloyd-Moulton price index PLMσ that will closely approximate the chained Fisher index PF for all periods. To approximate PF in period 2, choose σ close to 0.1; to approximate PF in period 3, choose σ close to 0.2; to approximate PF in period 4, choose σ between 0.2 and 0.3; and to approximate PF in period 5, choose c between 0.3 and 0.4. It should be noted, however, that if σ is chosen to equal to 0.3 and the resulting chained Lloyd-Moulton index PLM.3 is used to approximate the chained Fisher index PF, then a much better approximation to PF results than that provided by either the chained Laspeyres index (see PLM0 in the third column of Table 19.15) or the fixed base Laspeyres index (see PLM0 in the third column of Table 19.14).21 The tentative conclusions on the use of the Lloyd-Moulton index to approximate superlative indices that can be drawn from the above tables are:

  • the elasticity of substitution parameter σ which appears in the Lloyd-Moulton formula is unlikely to remain constant over time, and hence it will be necessary for statistical agencies to update their estimates of σ at regular intervals;

  • the use of the Lloyd-Moulton index as a real-time preliminary estimator for a chained superlative index seems warranted, provided that the statistical agency can provide estimates for chained superlative indices on a delayed basis. The Lloyd-Moulton index would provide a useful supplement to the traditional fixed base Laspeyres price index.

Table 19.15

Chained Fisher and chained Lloyd–Moulton indices

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Table 19.16

Diewert’s additive percentage change decomposition of the Fisher index

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Additive percentage change decompositions for the Fisher ideal index

19.32 The next formulae to be illustrated using the artificial data set are the additive percentage change decompositions for the Fisher ideal index, discussed in paragraphs 16.62 to 16.73 of Chapter 16.22 The chain links for the Fisher price index are first decomposed into additive components using the formulae (16.38) to (16.40). The results of the decomposition are listed in Table 19.16, Thus PF– 1 is the percentage change in the Fisher ideal chain link going from period t–1 to t, and the decomposition factor vFiΔPi=vFi(Pit−Pit−1) is the contribution to the total percentage change of the change in the i th price from pit−1 to pit for i = 1,2,…,6.

19.33 Table 19.16 shows that the price index going from period 1 to 2 grew about 40 per cent, and the major contributors to this change were the increases in the price of commodity 2, energy (18.77 per cent), and in commodity 5, traditional services (18.4 per cent). The increase in the price of traditional manufactured goods, commodity 3, contributed 5.8 per cent to the overall increase of 40.11 per cent. The decreases in the prices of high-technology goods (commodity 4) and high-technology services (commodity 6) offset the other increases by—3.51 per cent and–1.11 per cent going from period 1 to 2. Going from period 2 to 3, the overall change in prices was negative:–5.89 per cent. The reader can read across row 3 of Table 19.16 to see what was the contribution of the six component price changes to the overall price change. It is evident that a big price change in a particular component i, combined with a big expenditure share in the two periods under consideration will lead to a big decomposition factor, vFi.

19.34 The next set of computations to be illustrated using the artificial data set is the additive percentage change decomposition for the Fisher ideal index according to Van Ijzeren (1987, p. 6), which was mentioned in footnote 43 of Chapter 16.23 The price counterpart to the additive decomposition for a quantity index is:

P F ( p 0 , p 1 , q 0 , q 1 ) = Σ i = 1 n q F i * p i 1 Σ i = 1 n q F i * p i 0 ( 19.3 )

where the reference quantities need to be defined somehow. Van Ijzeren (1987, p. 6) showed that the following reference weights provide an exact additive representation for the Fisher ideal price index:

q F i * ≡ ( 1 / 2 ) q i 0 + { ( 1 / 2 ) q i 1 / Q F ( p 0 , p 1 , q 0 , q 1 ) } f o r i = 1 , 2 , … , 6 ( 19.4 )

where QF is the overall Fisher quantity index. Thus using the Van Ijzeren quantity weights qFi*, the following Van Ijzeren additive percentage change decomposition for the Fisher price index is obtained:

P F ( p 0 , p 1 , q 0 , q 1 ) − 1 = { Σ i = 1 6 q F i * p i 1 / Σ i = 1 6 q F i * p i 0 } − 1 = Σ i = 1 6 v F i * { p i 1 − p i 0 } ( 19.5 )

where the Van Ijzeren weight for commodity i, vFi*, is defined as

v F i * ≡ q F i * / Σ i = 1 6 q F i * p i 0 f o r i = 1 , 2 , … , 6 ( 19.6 )
Table 19.17

Van Ijzeren’s decomposition of the Fisher price index

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Table 19.18

The Lowe and Young indices, the fixed base Laspeyres, Paasche and Fisher indices, and the chained Laspeyres, Paasche and Fisher indices

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19.35 The chain links for the Fisher price index will be decomposed into price change components using the formulae (19.4) to (19.6), listed above. The results of the decomposition are listed in Table 19.17. Thus PF— 1 is the percentage change in the Fisher ideal chain link going from period t 1 to t and the Van Ijzeren decomposition factor vFi*Δpi is the contribution to the total percentage change of the change in the i th price from pit−1 to for 1,2,…, 6.

19.36 Comparing the entries in Tables 19.16 and 19.17, it can be seen that the differences between the Diewert and Van Ijzeren decompositions of the Fisher price index are very small. The maximum absolute difference between the vFjΔpi and vFi*Δpi is only 0.0018 (about 0.2 percentage points) and the average absolute difference is 0.0003. This is somewhat surprising given the very different nature of the two decompositions.24 As was mentioned in footnote 43 of Chapter 16, the Van Ijzeren decomposition of the chain Fisher quantity index is used by the Bureau of Economic Analysis in the United States.25

The Lowe and Young indices

19.37 Recall that the Lowe index was defined by equation (15.15) in Chapter 15. If it is desired to compare the prices in period t with those in period 0, the formula for the Lowe index is given by equation (19.7) below:

P L o ( p 1 , p t , p b ) ≡ Σ i = 1 6 p i t q i b / Σ i = 1 6 p i 0 q i b t = 1 , 2 , … , 5 ( 19.7 )

where qb≡[q1b,q2b,....,q6b] is the quantity vector pertaining to a base period b which is prior to period 0, the base period for prices. This index will be computed for periods t equal to 3 to 5 for the artificial data set where the quantity reference period b is taken to be period 1 and the price reference period 0 is taken to be period 3; see the column with the heading PLo in Table 19.18.

19.38 For comparison purposes, the fixed base Laspeyres, Paasche and Fisher indices are also calculated for periods 3, 4 and 5, where period 3 is treated as the base period; see the columns with the headings PL, PP and PF respectively. The chained Laspeyres, Paasche and Fisher indices are also calculated for periods 3, 4 and 5, and listed in Table 19.18; see the columns with the headings PLCH, PPCH and PFCH respectively. Table 19.18 shows that the Lowe index is higher than all six of these comparison indices in periods 4 and 5. In particular, the Lowe index PLO is greater than the fixed base Laspeyres index PL for periods 4 and 5, which is consistent with the inequality (15.37) in Chapter 15, where it was argued that the Lowe index would exceed the Laspeyres index if there were long-run trends in prices. Compared with the preferred fixed base or chained Fisher ideal target indices, PF or PFCH, the Lowe index has a considerable upward bias for this trending artificial data set.

19.39 The Young index was defined by equation (15.48) in Chapter 15 and, for convenience, this definition is repeated below:

P Y ( p 0 , p t , s b ) ≡ Σ i = 1 n s i b ( p i t / p i 0 ) ( 19.8 )

The base period b expenditure shares for the commodities are the sib in equation (19.8) and the price reference period is period 0. This Young index will be computed for periods t equal to 3 to 5 for the artificial data set, where the quantity reference period b is taken to be period 1 and the price reference period 0 is taken to be period 3; see the column with the heading PY in Table 19.18.

19.40 For periods 4 and 5, the Young index is below the corresponding values for the fixed base Laspeyres index.26 For period 4, the Young index is 0.9396, which is below the corresponding value for the Fisher index, which is 0.9624. However, for period 5, the Young index is 0.9794, which is above the corresponding values for the two target Fisher indices, which are 0.9244 for the fixed base index and 0.9273 for the chained index. Thus, although the direction of the bias in the Young index is not always the same, it can be seen that it has substantial biases for the artificial data set compared to the preferred target indices.

Mid-year indices based on the Lowe formula

19.41 Recall the Lowe index formula (19.7). In most applications of the formula by statistical agencies, the quantity vector q will be taken from a period that is prior to the base period for prices, which is period 1 in the artificial data set. It is also possible, however, to use the formula as a type of mid-year index, where the reference quantity vector q could be taken to be an average of the quantity vectors pertaining to periods 1 to 5. This possible use of the formula will be explored in the present section. Thus the first Lowe index, PLo1, sets q in formula (19.7) equal to q1, the period i quantity vector in the artificial data set. This index turns out to be identical to the fixed base Laspeyres index PL, which was listed earlier in Table 19.4. The second Lowe index, PLO2, sets q in formula (19.7) equal to the average of the period 1 and 2 quantity vectors, (1/2)(q1 + q2).27> The third Lowe index, PLO3, sets q equal to the average of the period 1 to 3 quantity vectors, (1/3)(q1+ q2 + q3). The fourth Lowe index, PLO4, sets q equal to the average of the period 1 to 4 quantity vectors, (1/4)(ql +q2 + q3 + q4). Finally, the fifth Lowe index, PLO5, sets q equal to the average of the period 1 to 5 quantity vectors, (1/5)(q1+ q2 + q3 + q4 + q5).28 The resulting five Lowe type indices are listed in Table 19.19.

19.42 The mid-year index PMY ≡ PLO(p1, pt, q3) was defined in paragraphs 15.49 to 15.53 of Chapter 15; it is a Lowe type index with the “representative” quantity vector q chosen to be q3, the quantity vector that pertains to the middle period in the span of periods under consideration (which is periods 1 to 5 in the numerical example). It is listed as the seventh column in Table 19.18.29 The mid-year index and the five Lowe indices are compared to two of the “best” target indices, the chain Törnqvist and chain Fisher indices, PT and PF listed in the last two columns of Table 19.19.

19.43 From Table 19.19, it can be seen that none of the Lowe type indices (or the mid-year index) are very close to the two target indices (the chain Törnqvist and chain Fisher) for all periods.30 With less extreme data sets, however, it is quite possible that the fifth Lowe index and the mid-year index could form adequate approximations to the target indices.

19.44 With strong trends in the price data and normal consumer substitution responses, it is unlikely that Lowe type indices, based on averages of the quantity data pertaining to the first few periods in a long time series of data, will be able to provide an adequate approximation to a chained superlative index. In general, this type of Lowe index will suffer from an upward bias compared to the target index, as can be seen from Table 19.19.

Young-type indices

19.45 Recall that the Young index was defined by equation (15.48) in Chapter 15, or equation (19.8) above. If it is desired to compare the prices in period t with those in period 1, the formula for the Young index is given by equation (19.9):

P Y ( p 0 , p t , s b ) ≡ Σ i = 1 6 s i b ( p i t / p i 1 ) f o r t = 1 , 2 , … , 5 ( 19.9 )

where the expenditure share vector sb≡[S1b,…,S6b] is “representative” for the span of periods under consideration. In most applications of the formula by statistical agencies, the base period expenditure share vector sb will be taken from a period that is prior to the base period for prices, which is period 1 in the artificial data set. For illustrative purposes, rather than adding new data to the artificial data set, the reference share vector sb will be taken to be an average of the expenditure share vectors pertaining to periods 1 to 5. Thus, the first Young-type index, PY1, sets sb in formula (19.9) equal to s1 the period 1 expenditure share vector in the artificial data set. This index turns out to be identical to the fixed base Laspeyres index PL, shown in Table 19.4. The second Young-type index, PY2, sets sb in formula (19.9) equal to the average of the period 1 and 2 share vectors, (1/2)(s1 + s2). The third Young-type index, PY3, sets sb equal to the average of the period 1 to 3 share vectors, (1/3)(s1 +s2 + s3). The fourth Young-type index, PY4, sets equal to the average of the period 1 to 4 share vectors, (1/4)(s1 + s2+ s3 +s4). Finally, the fifth Young-type index, Py5, sets sb equal to the average of the period 1 to 5 share vectors, (1/5)(s1 + s2 + s3 + s4 + s5). The resulting five Young type indices are listed in Table 19.20 below. These indices are compared to two of the “best” target indices, the chained Törnqvist and chained Fisher indices, PT and PF listed in the last two columns of Table 19.20.

19.46 Table 19.20 shows that all the Young-type indices exhibit a substantial upward bias compared to the target chain Törnqvist and Fisher indices, PT and PF. Comparing Table 19.19 with Table 19.20, it can be seen that the bias in the Young-type indices becomes bigger as the expenditure shares become more representative of all five periods, whereas the upward bias in the Lowe-type indices tends to become smaller as the reference quantity vector became more representative of all periods.

Table 19.19

The five Lowe indices, the mid-year index, and the Törnqvist and Fisher chain indices

article image
Table 19.20

The five Young-type indices and the Törnqvist and Fisher chain indices

article image

19.47 Note that the Young type indices PY2 to PYS are all bigger in magnitude than PY1, which is the ordinary fixed base Laspeyres index. It must be recognized, however, that these Young type indices are not the type of Young index that is computed by statistical agencies, in which the weight reference period precedes the price reference period. As discussed in paragraphs 19.39 to 19.42, this latter type of Young index could be above or below the corresponding fixed base Laspeyres index.

19.48 The results of this section and the previous one can be summarized as follows: it appears to be a useful exercise to attempt to find quantity weights for the Lowe formula that are representative for the entire period covered by the index, but it does not appear to be useful to do the same for the Young formula.

1

“Asymmetric weights” means that the quantity or value weights for the prices come from only one of the two periods being compared.

2

“Symmetric weights” means that the quantity or value weights for the prices enter the index number formula in a symmetric or even-handed way.

3

Recall from Chapter 17 that there is a separate Lloyd–Moulton index for each estimated elasticity of substitution parameter σ that is inserted into the formula.

4

Note, however, that the expenditure share of agricultural products shows a downward trend over time as the economy develops and shifts into services.

5

This is an example of the price bouncing phenomenon noted by Szulc (1983). Note that the fluctuations in the price of energy that are built into the data set are not that unrealistic: in the past four years, the price of a barrel of crude oil has fluctuated in the range US$12 to US$40.

6

This corresponds roughly to the experience of most industrialized countries over the period from 1973 to the mid-1990s. Thus, roughly five years of price movement are compressed into one of our periods.

7

According to the theorem of the arithmetic and geometric mean; see Hardy, Littlewood and Pólya (1934, p. 17).

8

The problem with the evenly weighted geometric mean is that the price declines in high-technology goods and services are given the same weighting as the price changes in the other four commodities (which have rising or stationary price changes), but the expenditure shares of the high-technology commodities remain rather small throughout the five periods. Thus weighted price indices do not show the rate of overall price decrease that the unweighted Jevons index shows. These somewhat negative comments on the use of the unweighted geometric mean as an index number formula at higher levels of aggregation do not preclude its use at the very lowest level of aggregation, where a strong axiomatic justification for the use of this formula can be given. If probability sampling is used at the lowest level of aggregation, then the unweighted geometric mean essentially becomes the logarithmic Laspeyres index.

9

For many data sets, the chained Carli can be expected to be above the corresponding fixed base Carli; see Szulc (1983).

10

Vartia (1978, p. 272) used the terms logarithmic Laspeyres and logarithmic Paasche, respectively.

12

These inequalities were noted by Fisher (1922, p. 92) and Vartia (1978, p. 278).

13

These inequalities were also noted by Fisher (1922, p. 92) and Vartia (1978, p. 278).

14

Diewert (1978, p. 897) showed that the Drobisch-Sidgwick-Bowley price index approximates any superlative index to the second order around an equal price and quantity point; i.e., PSB is a Pseudo-superlative index. Straightforward computations show that the Marshall–Edgeworth index PME is also pscudo-superlative.

15

In other periods, the differences were nevertheless larger. On average over the last four periods, the chain Fisher and the chain Törnqvist indices differed by 0.0025 percentage points.

16

More precisely, the superlative quadratic mean of order r price indices Pr defined by equation (17.35) and the implicit quadratic mean of order r price indices Pr* defined by equation (17.32) will generally closely approximate each other, provided that r is in the interval 0 ≤ r ≤ 2.

17

Alterman, Diewert and Feenstra (1999) also used this methodology in the context of estimating superlative international trade price indices.

18

Since there is still a considerable amount of dispersion among the fixed base superlative indices and practically no dispersion between the chained superlative indices, the Fisher chain index is taken as the target index rather than any of the fixed base superlative indices.

19

This follows from Schlömilch’s (1858) inequality again.

20

Unfortunately, for this data set, neither the fixed base Laspeyres index PL = PLM0 nor the fixed base weighted geometric index PGL = PLM1 is very close to the chain Fisher index for all periods. For less extreme data sets, the fixed base Laspeyres and fixed base geometric indices will be closer to the chained Fisher index.

21

For this particular data set, the fixed base or chained geometric indices using either the expenditure weights of period 1 (see the last column of Table 19.14) or using the weights of the previous period (see the last column of Table 19.15) do not approximate the chained Fisher index very closely. For less extreme data sets, however, the use of chained Laspeyres or geometric indices may approximate a chained superlative index adequately.

23

See Reinsdorf, Diewert and Ehemann (2002) for additional information on this decomposition

24

Reinsdorf, Diewert and Ehemann (2002) nevertheless show that the terms in the two decompositions approximate each other to the second order around any point where the two price vectors are equal and where the two quantity vectors are equal.

26

It is noted in Chapter 15 that the Young index can be above or below the corresponding fixed base Laspeyres index, depending on the responsiveness of expenditure shares to changes in prices.

27

This is the Lowe index for the artificial data set, which will probably be the most comparable to the type of Lowe index currently computed by statistical agencies.

28

This is Walsh’s (1901, p. 431) multi-year fixed basket index, where the quantity vector is chosen to be the arithmetic average of the quantity vectors in the lime period under consideration.

29

It can be verified that if there are exact linear time trends in the quantity data, then the mid-year index PMY will be exactly equal to the fifth Lowe index, PLO5.

30

The fourth Lowe index PLO4 and the mid-year index PMY appear to be the closest to the target indices.

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Cover Consumer Price Index Manual
Consumer Price Index Manual
Theory and Practice
ISBN:
9789221136996
ISSN:
2663-3744
Publication Date:
25 Aug 2004
Publisher:
International Monetary Fund
DOI:
https://doi.org/10.5089/9789221136996.069
Pages:
572

  • Abraham, K.G., J.S. Greenlees and B.R. Moulton. 1998. “Working to Improve the Consumer Price Index”, in Journal of Economic Perspectives, Vol. 12, No. 1, pp. 27–36.

    • Search Google Scholar
    • Export Citation

  • Aczél, J. 1987. A Short Course on Functional Equations (Dordrecht: Reidel Publishing Co.).

  • Advisory Commission to Study the Consumer Price Index. 1995. Toward a More Accurate Measure of the Cost of Living, Interim Report to the Senate Finance Committee, Sep. 15 (Washington, D.C.).

    • Search Google Scholar
    • Export Citation

  • Aizcorbe, A.M., and P.C. Jackman, 1993. “The commodity substitution effect in CPI data, 1982–91”, in Monthly Labor Review, Vol. 116, No. 12, pp. 25–33.

    • Search Google Scholar
    • Export Citation

  • Aizcorbe, A., C. Corrado and M. Doms. 2001. Constructing Price and Quantity Indexes for High Technology Goods, Industrial Output Section, Division of Research and Statistics (Washington, D.C.: Board of Governors of the Federal Reserve System).

    • Search Google Scholar
    • Export Citation

  • Alterman, W.F., W.E. Diewert and R.C. Feenstra. 1999. International Trade Price Indexes and Seasonal Commodities (Washington, D.C.: Bureau of Labor Statistics).

    • Search Google Scholar
    • Export Citation

  • Anderson, R.G., B.E. Jones and T. Nesmith. 1997. “Building New Monetary Services Indexes: Concepts, Data and Methods”, in Federal Reserve Bank of St. Louis Review, Vol. 79, No. 1, pp. 53–83.

    • Search Google Scholar
    • Export Citation

  • Ardilly, P. and F. Guglielmetti, 1993. “La précision de l’indice des prix: mesure et optimisation”, in Economie et Statistique. No. 267, juillet.

    • Search Google Scholar
    • Export Citation

  • Arguea, N.M., C. Haseo and G.A. Taylor. 1994. “Estimating Consumer Preferences using Market Data: An Application to U.S. Automobile Demand”, in Journal of Applied Econometrics, Vol. 9, pp. 1–18.

    • Search Google Scholar
    • Export Citation

  • Armknecht, P.A. 1996. Improving the Efficiency of the U.S. CPI, Working Paper No. 96/103 (Washington, D.C.: IMF).

  • Armknecht, P.A., and D. Weyback. 1989. “Adjustments for Quality Change in the U.S. Consumer Price Index”, in Journal of Official Statistics, Vol. 5, No. 2, pp. 107–123.

    • Search Google Scholar
    • Export Citation

  • Armknecht, P.A., and D. Weyback. and F. Maitland-Smith. 1999. Price Imputation and Other Techniques for Dealing with Missing Observations, Seasonality and Quality Change in Price Indices, Working Paper No. 99/78 (Washington, D.C.: IMF), June. Available at: http://www.imf.org/external/pubs/ft/wp/1999/wp9978.pdf.

    • Search Google Scholar
    • Export Citation

  • Armknecht, P.A., and D. Weyback. and F. Maitland-Smith. W.F. Lane and K.J. Stewart. 1997. “New Products and the U.S. Consumer Price Index”, in R.C. Feenstra and M.D. Shapiro (eds.): Scanner Data and Price Indexes, NBER Studies in income and Wealth (Chicago, IL: University of Chicago Press, 2003), pp. 375–391.

    • Search Google Scholar
    • Export Citation

  • Arrow, K.J., H.B. Chenery, B.S. Minhas and R.M. Solow. 1961. “Capital–Labor Substitution and Economic Efficiency”, in Review of Economics and Statistics, Vol. 63, pp. 225–250.

    • Search Google Scholar
    • Export Citation

  • Astin, J. 1999. “The European Union Harmonized Indices of Consumer Prices. HICP)”, in R. Gudnason and T. Gylfadottir (eds.): Proceedings of the Ottawa Group Fifth Meeting, Reykjavik, Iceland, 25–27 Aug.; also published in Statistical Journal of the United Nations ECE, Vol. 16, pp. 123–135. Available at: http://www.statcan.ca/secure/english/ottawagroup/.

    • Search Google Scholar
    • Export Citation

  • Astin, J. 2001. New Uses of PPPs within the European Union, Paper presented at the Joint World Bank-OECD Seminar on Purchasing Power Parities: Recent Advances in Methods and Applications, (Washington, D.C., Jan. 30–Feb. 2.

    • Search Google Scholar
    • Export Citation

  • Aten, B., R. Summers and A. Heston. 2001. An Explanation of Stability in Country Price Structures: Implications for Spatial–temporal Comparisons, Paper presented at the Joint World Bank-OECD Seminar on Purchasing Power Parities: Recent Advances in Methods and Applications, (Washington, D.C., Jan. 30–Feb. 2.

    • Search Google Scholar
    • Export Citation

  • Australian Bureau of Statistics. 1997. An Analytical Framework for Price Indexes in Australia, Information Paper, Catalogue No. 6421.0. Available at: http://www.abs.gov.au.

    • Search Google Scholar
    • Export Citation

  • Australian Bureau of Statistics. 2000. Price Index and The New Tax System, Information Paper, Catalogue No. 6425.0. Available at: http://www.abs.gov.au.

    • Search Google Scholar
    • Export Citation

  • Australian Bureau of Statistics. 2003. Australian Consumer Price Index: Concepts, Sources and Methods, Catalogue No. 6461.0. Available at: http://www.abs.gov.au/.

    • Search Google Scholar
    • Export Citation

  • Bailey, M.J., Muth, R.F. and Nourse, H.O. 1963. “A Regression Method for Real Estate Price Construction”, in Journal of the American Statistical Association, Vol. 58, pp. 933–942..

    • Search Google Scholar
    • Export Citation

  • Baker, D. 1998. “Does the CPI Overstate Inflation? An Analysis of the Boskin Commission Report”, in D. Baker (ed.): Getting Prices Right (Washington, D.C.: Economic Policy Institute), pp. 79–155.

    • Search Google Scholar
    • Export Citation

  • Baldwin, A. 1990. “Seasonal Baskets in Consumer Price Indexes”, in Journal of Official Statistics, Vol. 6, No. 3, pp. 251–273.

  • Balk, B.M. 1980a. “Seasonal Products in Agriculture and Horticulture and Methods for Computing Price Indices”, in Statistical Studies No. 24 (The Hague: Netherlands Central Bureau of Statistics).

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 1980b. “Seasonal Commodities and the Construction of Annual and Monthly Price Indexes”, in Statistische Hefte, Vol. 21, pp. 110–116.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 1980c. “A Method for Constructing Price Indices for Seasonal Commodities”, in The Journal of the Royal Statistical Society Series A, Vol. 143, pp. 68–75.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 1981. “A Simple Method for Constructing Price Indices for Seasonal Commodities”, in Statistische Hefte, Vol. 22, pp. 72–78.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 1983. “Does There Exist a Relation between Inflation and Relative Price Change Variability? The Effect of the Aggregation Level”, in Economic Letters, Vol. 13, pp. 173–180.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 1985. “A Simple Characterization of Fisher’s Price Index”, in Statistische Hefte, Vol. 26, pp. 59–63.

  • Balk, B.M. 1989a. “Changing Consumer Preferences and the Cost of Living Index: Theory and Nonparametric Expressions”, in Zeitschrift für Nationalökonomie, Vol. 50, No. 2, pp. 157–169.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 1989b. “On Calculating the Precision of Consumer Price Indices”, in Contributed Papers 47th Session of the ISI (Paris).

  • Balk, B.M. 1990. “On Calculating Cost-of-Living Index Numbers for Arbitrary income Levels”, in Econometrica, Vol. 58, No. 1, pp. 75–92.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 1994. On the First Step in the Calculation of a Consumer Price Index, Paper presented at First Meeting of the International Working Group on Price Indices, Ottawa, Oct. 31-Nov. 4. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 1995. “Axiomatic Price Index Theory: A Survey”, in International Statistical Review, Vol. 63, pp. 69–93.

  • Balk, B.M. 1996a. “A Comparison of Ten Methods for Multilateral International Price and Volume Comparisons”, in Journal of Official Statistics, Vol. 12, pp. 199–222.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 1996b. “Consistency in Aggregation and Stuvel Indices”, in The Review of income and Wealth, Vol. 42, pp. 353–363.

  • Balk, B.M. 1998a. Industrial Price, Quantity and Productivity Indices (Boston, MA: Kluwer Academic Publishers).

  • Balk, B.M. 1998b. On the Use of Unit Value Indices as Consumer Price Subindices, Paper presented at the Fourth Meeting of the International Working Group on Price Indices, (Washington, D.C., Apr. 22–24, Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 2000a. Divisia Price and Quantity Indexes 75 Years After, Draft Paper, Department of Statistical Methods (Voorburg: Statistics Netherlands).

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 2000b. On Curing the CPI’s Substitution and New Goods Bias, Research Paper 0005, Department of Statistical Methods (Voorburg: Statistics Netherlands).

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 2001. Aggregation Methods in International Comparisons: What have we Learned?, Report Series Research in Management ERS-2001–41-MKT, Erasmus Research Institute of Management (Rotterdam: Erasmus University).

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. 2002. Price Indexes for Elementary Aggregates: The Sampling Approach, Research Report, Methods and Informatics Department (Voorburg: Statistics Netherlands).

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. and W.E. Diewert. 2001. “A Characterization of the Törnqvist Price Index”, in Economics Letters, Vol. 73, pp. 279–281.

    • Search Google Scholar
    • Export Citation

  • Balk, B.M. and H.M.P. Kersten. 1986. “On the Precision of Consumer Price Indices Caused by the Sampling Variability of Budget Surveys”, in Journal of Economic and Social Measurement, Vol. 14, pp. 19–35.

    • Search Google Scholar
    • Export Citation

  • Bartik, T.J. 1988. “Measuring the Benefits of Land Improvements in Hedonic Models”, in Land Economics, Vol. 64, No. 2, pp. 172–183.

    • Search Google Scholar
    • Export Citation

  • Bascher, J. and T. Lacroix. 1999. Dishwashers and PCs in the French CPI: Hedonic Modeling, from Design to Practice, Paper presented at the Fifth Meeting of the International Working Group on Price Indices, Reykjavik, Aug. 25–27. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Baxter, M. (ed.). 1998. The Retail Prices Index. Technical Manual (London: Office for National Statistics, UK).

  • Bean, L.H. and O.C. Stine. 1924. “Four Types of Index Numbers of Farm Prices”, in Journal of the American Statistical Association, Vol. 19, pp. 30–35.

    • Search Google Scholar
    • Export Citation

  • Becker, G.S. 1965. “A Theory of the Allocation of Time”, in Economic Journal, Vol. 75, pp. 493–517.

  • Beidelman, C. 1973. Valuation of Used Capital Assets (Sarasota, FL: American Accounting Association).

  • Beidelman, C.. 1976. “Economic Depreciation in a Capital Goods Industry”, in National Tax Journal, Vol. 29, pp. 379–390.

  • Berndt, E.R. 1991. The Practice of Econometrics: Classic and Contemporary (Reading, MA: Addison-Wesley).

  • Berndt, E.R. D. Ling and M.K. Kyle. 2003. “The Long Shadow of Patent Expiration: Generic Entry and Rx to OTC Switches”, in M. Shapiro and R.C. Feenstra (eds.): Scanner Data and Price Indexes, NBER Studies in income and Wealth (Chicago, IL: University of Chicago Press), pp. 229–273.

    • Search Google Scholar
    • Export Citation

  • Berndt, E.R. D. Ling and M.K. Kyle. L.T. Bui, D.H, Lucking-Reiley and G.L. Urban. 1997. “The Roles of Marketing, Product Quality and Price Competition in the Growth and Composition of the U.S. Anti-Ulcer Drug Industry”, in T. Bresnahan and R.J. Gordon: The Economics of New Goods, NBER Studies in income and Wealth (Chicago and London: University of Chicago Press), pp. 277–232.

    • Search Google Scholar
    • Export Citation

  • Berndt, E.R. D. Ling and M.K. Kyle. L.T. Bui, D.H, Lucking-Reiley and G.L. Urban. Z. Griliches and N.J. Rappaport. 1995. “Econometric Estimates of Price Indexes for Personal Computers in the 1990s”, in Journal of Econometrics, Vol. 68, pp. 243–68.

    • Search Google Scholar
    • Export Citation

  • Berry S., J. Levinsohn and A. Pakes. 1995. “Automobile Prices in Market Equilibrium”, in Econometrica, Vol. 63, No. 4, pp. 841–890; also published as NBER Working Paper No. W4264, July 1996, available at: http://www.nber.org.

    • Search Google Scholar
    • Export Citation

  • Beuerlein, I. 2001. The German consumer price index for telecommunication services: a user profile approach for mobile technology and Internet access, Paper presented at the Sixth Meeting of the International Working Group on Price Indices, Canberra, Apr. 2–6. Available at: http://www.ottawagroup.org/.

    • Search Google Scholar
    • Export Citation

  • Bode, B. and van J. Dalén. 2001. Quality-Corrected Price Indexes of New Passenger Cars in the Netherlands, 1990–1999, Paper presented at the Sixth Meeting of the International Working Group on Price Indices, Canberra, Apr. 2–6. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Böhm-Bawerk. E.V, 1891. The Positive Theory of Capital, translated from the original German edition of 1888 by W. Smart (New York: G.E. Stechert).

    • Search Google Scholar
    • Export Citation

  • Boon, M. 1998. “Sampling designs in compiling consumer price indices: current practices at EU statistical institutes”, in Research in Official Statistics, Vol. 1, No. 2, pp. 39–52.

    • Search Google Scholar
    • Export Citation

  • Bortkiewicz, L.V. 1923. “Zweck und Struktur einer Preisindexzahl”, in Nordisk Statistisk Tidsskrift 2, pp. 369–408.

  • Boskin, M.J. (Chair), E.R. Dullberger, R.J. Gordon, Z. Griliches and D.W. Jorgenson. 1996. Final Report of the Commission to Study the Consumer Price Index, U.S. Senate, Committee on Finance (Washington, D.C.: U.S. Government Printing Office).

    • Search Google Scholar
    • Export Citation

  • Boskin, M.J. (Chair), E.R. Dullberger, R.J. Gordon, Z. Griliches and D.W. Jorgenson. 1998. “Consumer Prices in the Consumer Price Index and the Cost of Living”, in Journal of Economic Perspectives, Vol. 12, No. 1, pp. 3–26.

    • Search Google Scholar
    • Export Citation

  • Bowley, A.L. 1899. “Wages, Nominal and Real”, in R.H.I. Palgrave, (ed.): Dictionary of Political Economy, Volume 3 (London: Macmillan), pp. 640–651.

    • Search Google Scholar
    • Export Citation

  • Bowley, A.L. 1901. Elements of Statistics (Westminster: Orchard House).

  • Bowley, A.L. 1919. “The Measurement of Changes in the Cost of Living”, in Journal of the Royal Statistical Society, Vol. 82, pp. 343–361.

    • Search Google Scholar
    • Export Citation

  • Bradley, R., B. Cook, S.E. Leaver and B. R. Moulton. 1997. An Overview of Research on Potential Uses of Scanner Data in the U.S. CPI, Paper presented at the Third Meeting of the International Working Group on Price Indices, Voorburg, Apr. 16–18. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Braithwait, S.D. 1980. “The Substitution Bias of the Laspeyres Price Index: An Analysis Using Estimated Cost-of-Living Indexes”, in American Economic Review, Vol. 70, No. 1, pp. 64–77.

    • Search Google Scholar
    • Export Citation

  • Bresnahan, T.F. 1997. “Comment”, in T.F. Bresnahan and R.J. Gordon (eds.): The Economics of New Goods, NBER Studies in income and Wealth (Chicago, IL: University of Chicago Press), pp. 237–247.

    • Search Google Scholar
    • Export Citation

  • Canning, J.B. 1929. The Economics of Accountancy (New York: The Ronald Press Co.).

  • Carli, G.R. 1804. “Del valore e della proporzione dei metalli monetati”, in Scrittori classici italiani di economia politica, Vol. 13 (Milano: G.G. Destefanis), pp. 297–366; originally published in 1764.

    • Search Google Scholar
    • Export Citation

  • Carruthers, A.G., D.J. Sellwood and P.W. Ward. 1980. “Recent Developments in the Retail Prices Index”, in The Statistician, Vol. 29, pp. 1–32.

    • Search Google Scholar
    • Export Citation

  • Cassel, E. and R. Mendelsohn. 1985. “On the Choice of Functional Forms for Hedonic Price Equations: Comment”, in Journal of Urban Economics, Vol. 18, Sep., pp. 135–142.

    • Search Google Scholar
    • Export Citation

  • Castles, I. 1997. The OECD-EUROSTAT PPP Program: Review of Practice and Procedures (Paris: OECD).

  • Caves, D.W., L.R. Christensen and W.E. Diewert, 1982a. “The Economic Theory of Index Numbers and the Measurement of Input, Output and Productivity”, in Econometrica, Vol. 50, 1393–1414.

    • Search Google Scholar
    • Export Citation

  • Caves, D.W., L.R. Christensen and W.E. Diewert, L.R. Christensen and W.E. Diewert. 1982b. “Multilateral Comparisons of Output, Input and Productivity using Superlative Index Numbers”, in Economic Journal, Vol. 92, pp. 73–86.

    • Search Google Scholar
    • Export Citation

  • Cecchetti, S.G. 1997. “Measuring Inflation for Central Bankers”, in Federal Reserve Bank of St. Louis Review, Vol. 79, pp. 143–155.

    • Search Google Scholar
    • Export Citation

  • Christensen, L.R. and D.W. Jorgenson. 1969. “The Measurement of U.S. Real Capital Input, 1929–1967”, in Review of income and Wealth, Vol. 15, No. 4, pp. 293–320.

    • Search Google Scholar
    • Export Citation

  • Christensen, L.R. and D.W. Jorgenson. and L.J. Lau. 1971. “Conjugate Duality and the Transcendental Logarithmic Production Function”, in Econometrica, Vol. 39, pp. 255–256.

    • Search Google Scholar
    • Export Citation

  • Church, A.H. 1901. “The Proper Distribution of Establishment Charges, Part III”, in The Engineering Magazine, Vol. 21, pp. 904–912.

    • Search Google Scholar
    • Export Citation

  • Clements, K.W. and H.Y. Izan. 1981. “A Note on Estimating Divisia Index Numbers”, in International Economic Review, Vol. 22, pp. 745–747.

    • Search Google Scholar
    • Export Citation

  • Clements, K.W. and H.Y. Izan. and H.Y. Izan. 1987. “The Measurement of Inflation: A Stochastic Approach”, in Journal of Business and Economic Statistics, Vol. 5, pp. 339–350.

    • Search Google Scholar
    • Export Citation

  • Cobb, C. and P.H. Douglas. 1928. “A Theory of Production”, in American Economic Review, Vol. 18, pp. 39–165.

  • Cochran, W.G. 1977. Sampling Techniques, 3rd edition (New York: Wiley).

  • Cockburn, I.M. and A.H. Anis. 1998. Hedonic Analysis and Arthritic Drugs, Working Paper 6574 (Cambridge, MA: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation

  • Coggeshall, F. 1887. “The Arithmetic, Geometric and Harmonic Means”, in Quarterly Journal of Economics, Vol. 1, pp. 83–86.

  • Combris, P., S. Lecocqs and M. Visser. 1997. “Estimation of a Hedonic Price Equation for Bordeaux Wine: Does Quality Matter?”, in Economic Journal, Vol. 107, No. 441, pp. 390–402.

    • Search Google Scholar
    • Export Citation

  • Commission of the European Communities (Eurostat), IMF, OECD, United Nations and World Bank. 1993. System of National Accounts 1993 (Brussels/Luxembourg, New York, Paris, Washington, D.C.).

    • Search Google Scholar
    • Export Citation

  • Congressional Budget Office (CBO). 1994. Is the Growth of the CPI a Biased Measure of Changes in the Cost of Living?, CBO Paper, Oct. (Washington, D.C.).

    • Search Google Scholar
    • Export Citation

  • Crawford, A. 1998. “Measurement Biases in the Canadian CPI: An Update”, in Bank of Canada Review, Spring, pp. 39–56.

  • Cropper, M.L., L.L. Deck and K.E. McConnell. 1988. “On the Choice of Functional Form for Hedonic Price Functions”, in Review of Economics and Statistics, Vol. 70, No. 4, pp. 668 –675.

    • Search Google Scholar
    • Export Citation

  • Crump, N. 1924. “The Interrelation and Distribution of Prices and their Incidence Upon Price Stabilization”, in Journal of the Royal Statistical Society, Vol. 87, pp. 167–206.

    • Search Google Scholar
    • Export Citation

  • Cunningham, A.W.F. 1996. Measurement Bias in Price Indices: An Application to the UK’s RPI, Bank of England Working Paper 47 (London: Bank of England).

    • Search Google Scholar
    • Export Citation

  • Curry, B., P. Morgan and M. Silver. 2001. “Hedonic Regressions: Misspecification and Neural Networks”, in Applied Economics, Vol. 33, pp. 659–671.

    • Search Google Scholar
    • Export Citation

  • Czinkota, M.R. and I. Ronkainen. 1997. “International Business and Trade in the Next Decade: Report from a Delphi Study”, in Journal of International Business Studies, Vol. 28, No. 4, pp. 827–844.

    • Search Google Scholar
    • Export Citation

  • Dalén, J. 1992. “Computing Elementary Aggregates in the Swedish Consumer Price Index”, in Journal of Official Statistics, Vol. 8, pp. 129–147.

    • Search Google Scholar
    • Export Citation

  • Dalén, J. 1994. Sensitivity Analyses for Harmonizing European Consumer Price Indices, Paper presented at the First Meeting of the International Working Group on Price Indices, Ottawa, Oct. 31-Nov. 4. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Dalén, J. 1995. “Quantifying errors in the Swedish consumer price index”, in Journal of Official Statistics, Vol. 13, No. 3, pp. 347–356.

    • Search Google Scholar
    • Export Citation

  • Dalén, J. 1997. Experiments with Swedish Scanner Data, Paper presented at the Third Meeting of the International Working Group on Price Indices, Voorburg, Apr. 16–18. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Dalén, J. 1998a. On the Statistical Objective of a Laspeyres Price Index, Paper presented at the Fourth Meeting of the International Working Group on Price Indices, Washington, D.C., Apr. 22–24. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Dalén, J. 1998b. “Studies on the Comparability of Consumer Price Indices”, in International Statistical Review, Vol. 66, No. 1, pp. 83–113.

    • Search Google Scholar
    • Export Citation

  • Dalén, J. 1999a. “On Reliability, Uncertainty and Bias in Consumer Price Indexes”, in M. Silver and D. Fenwick (eds.): Proceedings of the Measurement of Inflation Conference (Cardiff: Cardiff University), pp. 184–190.

    • Search Google Scholar
    • Export Citation

  • Dalén, J. 1999b. A note on the Variance of the Sample Geometric Mean, Research Report 1991: 1, Department of Statistics (Stockholm: Stockholm University).

    • Search Google Scholar
    • Export Citation

  • Dalén, J. and O. Muelteel. 1998. Variance estimation in the Luxembourg CPI, Cellule “Statistique et décision” (Luxembourg: Centre de Recherche Public-Centre Universitaire).

    • Search Google Scholar
    • Export Citation

  • Dalén, J. and E. Ohlsson. 1995. “Variance Estimation in the Swedish Consumer Price Index”, in Journal of Business and Economic Statistics, Vol. 13, No. 3, pp. 347–356.

    • Search Google Scholar
    • Export Citation

  • Dalton, K.V., J.S. Greenlees, and K.J. Stewart. 1998. “Incorporating a Geometric Mean Formula into the CPI”, in Monthly Labor Review, Vol. 121, No. 10, pp. 3–7.

    • Search Google Scholar
    • Export Citation

  • Davies, G.R. 1924. “The Problem of a Standard Index Number Formula”, in Journal of the American Statistical Association, Vol. 19, pp. 180–188.

    • Search Google Scholar
    • Export Citation

  • Davies, G.R. 1932. “Index Numbers in Mathematical Economics”, in Journal of the American Statistical Association, Vol. 27, pp. 58–64.

    • Search Google Scholar
    • Export Citation

  • de Haan, J. 2001. Generalised Fisher Price Indexes and the Use of Scanner Data in the CPI, Unpublished Paper (Voorburg: Statistics Netherlands).

    • Search Google Scholar
    • Export Citation

  • de Haan, J. 2003. Time Dummy Approaches to Hedonic Price Measurement, Paper presented at the Seventh Meeting of the International Working Group on Price Indices, Paris, May 27–29. Available at: http://www.insee.fr/.

    • Search Google Scholar
    • Export Citation

  • de Haan, J. and E. Opperdoes. 1997. Estimation of the Coffee Price Index Using Scanner Data: Simulation of Official Practices, Paper presented at the Third Meeting of the International Working Group on Price Indices, Voorburg, Apr. 16–18. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • de Haan, J. and E. Opperdoes, and C. Schut. 1997. Item Sampling in the Consumer Price Index: A Case Study using Scanner Data, Research Report (Voorburg: Statistics Netherlands).

    • Search Google Scholar
    • Export Citation

  • de Haan, J. and E. Opperdoes, and C. Schut. 1999. “Item Selection in the Consumer Price Index: Cut-off Versus Probability Sampling”, in Survey Methodology, Vol. 25, No. 1, pp. 31–41.

    • Search Google Scholar
    • Export Citation

  • Deaton, A. 1998. “Getting prices right: What should be done?”, in Journal of Economic Perspectives, Vol. 12, No. 1, pp. 37–46.

  • Denny, M. 1974. “The Relationship Between Functional Forms for the Production System”, in Canadian Journal of Economics, Vol. 7, pp. 21–31.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1974a. “Applications of Duality Theory”, in M.D. Intriligator and D.A. Kendrick (eds.): Frontiers of Quantitative Economics, Vol. II (Amsterdam: North-Holland) pp. 106–171.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1974b. “Intertemporal Consumer Theory and the Demand for Durables”, in Econometrica, Vol. 42, pp. 497–516.

  • Diewert, W.E. 1976. “Exact and Superlative Index Numbers”, in Journal of Econometrics, Vol. 4, pp. 114–145.

  • Diewert, W.E. 1978. “Superlative Index Numbers and Consistency in Aggregation”, in Econometrica, Vol. 46, pp. 883–900.

  • Diewert, W.E. 1980, “Aggregation Problems in the Measurement of Capital”, in D. Usher (ed.): The Measurement of Capital, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 433–528.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1983a. “The Theory of the Cost of Living Index and the Measurement of Welfare Change”, in W.E. Diewert and C. Montmarquette (eds.): Price Level Measurement (Ottawa: Statistics Canada), pp. 163–233; reprinted in W.E. Diewert (ed.): Price Level Measurement (Amsterdam: North-Holland, 1990), pp. 79–147.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1983b. “The Theory of the Output Price Index and the Measurement of Real Output Change”, in W.E. Diewert and C. Montmarquette (eds.): Price Level Measurement (Ottawa: Statistics Canada), pp. 1049–1113.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1983c. “The Treatment of Seasonality in a Cost of Living Index”, in W.E. Diewert and C. Montmarquette (eds.): Price Level Measurement (Ottawa: Statistics Canada), pp. 1019–1045.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1986. Microeconomic Approaches to the Theory of International Comparisons, Technical Working Paper No. 53 (Cambridge, MA: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1992a. “Fisher Ideal Output, Input and Productivity Indexes Revisited”, in Journal of Productivity Analysis, Vol. 3, pp. 211–248.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1992b. “Exact and Superlative Welfare Change Indicators”, in Economic Inquiry, Vol. 30, pp. 565–582.

  • Diewert, W.E. 1993a. “The Early History of Price Index Research”, in W.E. Diewert and A.O. Nakamura (eds.): Essays in Index Number Theory, Vol. 1, Contributions to Economic Analysis 217 (Amsterdam: North-Holland), pp. 33–65.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1993b. “Duality Approaches to Microeconomic Theory”, in W.E. Diewert and A.O. Nakamura (eds.): Essays in Index Number Theory, Vol. 1, Contributions to Economic Analysis 217 (Amsterdam: North-Holland), pp. 105–175.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1993c. “Symmetric Means and Choice under Uncertainty”, in W.E. Diewert and A.O. Nakamura (eds.): Essays in Index Number Theory, Vol. 1, Contributions to Economic Analysis 217 (Amsterdam: North-Holland), pp. 355–433.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1993d. “Overview of Volume 1”, in W.E. Diewert and A.O. Nakamura (eds.): Essays in Index Number Theory, Vol. 1, Contributions to Economic Analysis 217 (Amsterdam: North-Holland) pp. 1–31.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1995a. Axiomatic and Economic Approaches to Elementary Price Indexes, Discussion Paper No. 95–01, Department of Economics (Vancouver: University of British Columbia). Available at: http://www.econ.ubc.ca.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1995b. On the Stochastic Approach to Index Numbers, Discussion Paper No. 95–31, Department of Economics (Vancouver: University of British Columbia). Available at: http://www.econ.ubc.ca.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1996a. “Price and Volume Measures in the National Accounts”, in J. Kendrick (ed.): The New System of National Economic Accounts (Norwell, MA: Kluwer Academic Publishers), pp. 237–285.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1996b. Seasonal Commodities, High Inflation and Index Number Theory, Discussion Paper 96–06, Department of Economics (Vancouver: University of British Columbia).

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1996c. Sources of Bias in Consumer Price Indexes, Discussion Paper, School of Economics (Sydney: University of New South Wales).

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1997. “Commentary on Mathew D. Shapiro and David W. Wilcox: Alternative Strategies for Aggregating Price in the CPI”, in The Federal Reserve Bank of St. Louis Review, Vol. 79, No. 3, pp. 127–137.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1998a. “Index Number Issues in the Consumer Price Index”, in The Journal of Economic Perspectives, Vol. 12, No. 1, pp. 47–58.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1998b. “High Inflation, Seasonal Commodities and Annual Index Numbers”, in Macroeconomic Dynamics, Vol. 2, pp. 456–471.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 1999a. “Index Number Approaches to Seasonal Adjustment”, in Macroeconomic Dynamics, Vol. 3, pp. 48–68.

  • Diewert, W.E. 1999b. “Axiomatic and Economic Approaches to Multilateral Comparisons”, in A. Heston and R.E. Lipsey (eds.): International and Interarea Comparisons of Income. Output and Prices (Chicago, IL: University of Chicago Press), pp. 13–87.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 2000. Notes on Producing an Annual Superlative Index Using Monthly Price Data, Discussion Paper No. 00-08, Department of Economics (Vancouver: University of British Columbia). Available at: http://www.econ.ubc.ca.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 2001. “The Consumer Price Index and Index Number Purpose”, in Journal of Economic and Social Measurement, Vol. 27, pp. 167–248.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 2002a. “The Quadratic Approximation Lemma and Decompositions of Superlative Indexes”, in Journal of Economic and Social Measurement, Vol. 28, pp. 63–88.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 2002b. Similarity and Dissimilarity Indexes: An Axiomatic Approach, Discussion Paper No. 02-10, Department of Economics (Vancouver: University of British Columbia). Available at: http://www.econ.ubc.ca.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 2002c. “Harmonized Indexes of Consumer Prices: Their Conceptual Foundations”, in Swiss Journal of Economics and Statistics, Vol. 138, No. 4, pp. 547–637.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 2002d. Notes on Hedonic Producer Price Indexes, Unpublished Paper, Department of Economics (Vancouver: University of British Columbia), Jan.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 2002e. Hedonic Regressions: A Review of Some Unresolved Issues, Unpublished Paper, Department of Economics (Vancouver: University of British Columbia).

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 2003a. “Hedonic Regressions: A Consumer Theory Approach”, in R.C. Feenstra and M.D. Shapiro (eds.): Scanner Data and Price Indexes, NBER Studies in Income and Wealth (Chicago, IL: The University of Chicago Press), pp. 317–348.

    • Search Google Scholar
    • Export Citation

  • Diewert, W.E. 2003b. Measuring Capital, NBER Working Paper W9526 (Cambridge, MA: National Bureau of Economic Research).

  • Diewert, W.E. and D.A. Lawrence. 2000. “Progress in Measuring the Price and Quantity of Capital”, in L.J. Lau (ed.): Econometrics Volume 2: Econometrics and the cost of Capital: Essays in Honor of Dale W. Jorgenson (Cambridge, MA: The MIT Press), pp. 273–326.

    • Search Google Scholar
    • Export Citation

  • Dikhanov, Y. 1997. The Sensitivity of PPP-Based Income Estimates to Choice of Aggregation Procedures, Unpublished Paper, International Economics Department (Washington, D.C.: World Bank), Jan.

    • Search Google Scholar
    • Export Citation

  • Dippo, C.S. and C.A. Jacobs. 1983. “Area Sampling Redesign for the Consumer Price Index”, in Proceedings of the Survey Research Methods Section, American Statistical Association, pp. 118–123.

    • Search Google Scholar
    • Export Citation

  • Divisia, F. 1926. L’indice monétaire et la théorie de la monnaie (Paris: Société anonyme du Recueil Sirey).

  • Drechsler, L. 1973, “Weighting of Index Numbers in Multilateral International Comparisons”, in Review of Income and Wealth, Vol. 19, pp. 17–34.

    • Search Google Scholar
    • Export Citation

  • Drobisch, M. W. 1871a. “Ueber die Berechnung der Veränderungen der Waarenpreise und des Geldwerths”, in Jahrbücher für Nationalökonomie und Statistik, Vol. 16, pp. 143–156.

    • Search Google Scholar
    • Export Citation

  • Drobisch, M. W. 1871b. “Ueber einige Einwürfe gegen die in diesen Jahrbüchern veröffentlichte neue Methode, die Veränderungen der Waarenpreise und des Geldwerths zu berechten”, in Jahrbücher für Nationalokonomie und Statistik, Vol. 16, pp. 416–427.

    • Search Google Scholar
    • Export Citation

  • Ducharme. L.M. 1997. “The Canadian Consumer Price Index and the Bias Issue: Present and Future Outlooks” in L.M. Ducharme (ed.): Bias in the CPI: Experiences from Five OECD Countries, Prices Division Analytical Series, No. 10 (Ottawa: Statistics Canada), pp. 13–24.

    • Search Google Scholar
    • Export Citation

  • Duggan, J. E. and R. Gillingham. 1999. “The Effect of Errors in the CPI on Social Security Finances”, in Journal of Business and Economic Statistics, Vol. 17, No. 2, pp. 161–169.

    • Search Google Scholar
    • Export Citation

  • Dulberger, E.R. 1989. “The Application of an Hedonic Model to a Quality-Adjusted Price Index For Computer Processors”, in D. Jorgenson and R. Landau (eds.): Technology and Capital Formation (Cambridge, MA: MIT Press).

    • Search Google Scholar
    • Export Citation

  • Dulberger, E.R. 1993. “Sources of Price Decline in Computer Processors: Selected Electronic Components”, in M. Foss, M.E. Manser and A.H. Young (eds.): Price Measurement and their Uses, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 103–124.

    • Search Google Scholar
    • Export Citation

  • Dutot, C. 1738. Réflections politiques sur les finances et le commerce, Vol. 1 (La Haye: Les freres Vaillant et N. Prevost).

  • Dwyer, L., P. Forsyth and D.S. Prasada Rao. 2001. PPPs and the Price Competitiveness of International Tourism Destinations, Paper presented at the Joint World Bank–OECD Seminar on Purchasing Power Parities: Recent Advances in Methods and Applications, Washington, D.C., Jan. 30–Feb. 2.

    • Search Google Scholar
    • Export Citation

  • Edgeworth, F.Y. 1888. “Some New Methods of Measuring Variation in General Prices”, in Journal of the Royal Statistical Society, Vol. 51, pp. 346–368.

    • Search Google Scholar
    • Export Citation

  • Edgeworth, F.Y. 1923. “The Doctrine of Index Numbers According to Mr. Correa Walsh”, in The Economic Journal, Vol. 11, pp. 343–351.

    • Search Google Scholar
    • Export Citation

  • Edgeworth, F.Y. 1925. Papers Relating to Political Economy, Vol. 1 (New York: Burt Franklin).

  • Edwards, R. 1997. “Measuring Inflation in Australia”, in L.M. Ducharme (ed.): Bias in the CPI: Experiences from Five OECD Countries, Prices Division Analytical Series, No. 10 (Ottawa: Statistics Canada), pp. 5–12.

    • Search Google Scholar
    • Export Citation

  • Ehemann, C., A.J. Katz and B.R. Moulton. 2002. “The Chain-Additivity Issue and the U.S. National Accounts”, in Journal of Economic and Social Measurement, Vol. 28, pp. 37–49.

    • Search Google Scholar
    • Export Citation

  • Eichhorn, W. 1978. Functional Equations in Economics (Reading, MA: Addison-Wesley Publishing Company).

  • Eichhorn, W. and J. Voeller. 1976. Theory of the Price Index, Lecture Notes in Economics and Mathematical Systems, Vol. 140 (Berlin: Springer-Verlag).

    • Search Google Scholar
    • Export Citation

  • Eldridge, L.P. 1999. “How price indexes affect BLS productivity measures”, in Monthly Labor Review, Vol. 122, No. 2, pp. 35–46.

  • Elteto, O. and P. Koves. 1964. “On an Index Number Computation Problem in International Comparison”, in Statisztikai Szemle, Vol. 42, pp. 507–518 (in Czech).

    • Search Google Scholar
    • Export Citation

  • Epple, D. 1987. “Hedonic Prices and Implicit Markets: Estimating Demand and Supply Functions for Differentiated Products”, in Journal of Political Economy, Vol. 95, pp. 59–80.

    • Search Google Scholar
    • Export Citation

  • European Foundation for Quality Management Excellence Mode. (Brussels: European Foundation for Quality Management). Available at: http://www.efqm.org.

  • Eurostat. 1993. Classification of Products by Activity in the European Economic Community (CPA) (Luxembourg).

  • Eurostat.. 2001a. Compendium of HICP Reference Documents (Luxembourg: Unit B3, Harmonisation of Price Indices), Mar.

  • Eurostat. 2001b. Handbook on Price and Volume Measures in National Accounts (Luxembourg: European Commission).

  • Feenstra, R.C. 1994. “New Product Varieties and the Measurement of International Prices”, in American Economic Review, Vol. 34, pp. 157–177.

    • Search Google Scholar
    • Export Citation

  • Feenstra, R.C. 1995. “Exact Hedonic Price Indices”, in Review of Economics and Statistics, Vol. 77, pp. 634–654.

  • Feenstra, R.C. and C.R. Shiells. 1997. “Bias in U.S. Import Prices and Demand”, in T.F. Bresnahan and R.J. Gordon (eds.): The Economics of New Goods, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago), pp. 249–276.

    • Search Google Scholar
    • Export Citation

  • Feenstra, R.C. and M.D. Shapiro. 2003. “High Frequency Substitution and the Measurement of Price Indexes”, in R.C. Feenstra and M.D. Shapiro (eds.): Scanner Data and Price Indexes, NBER Studies in Income and Wealth (Chicago, IL: The University of Chicago Press), pp. 123–146.

    • Search Google Scholar
    • Export Citation

  • Feenstra, R.C. and W.E. Diewert. 2001. Imputation and Price Indexes: Theory and Evidence from the International Price Program, Working Paper No. 335 (Washington, D.C.: Bureau of Labor Statistics). Available at: http://www.bls.gov.

    • Search Google Scholar
    • Export Citation

  • Fenwick. D. 1997. “The Boskin Report from a United Kingdom Perspective”, in L.M. Ducharme (ed.): Bias in the CPI: Experiences from Five OECD Countries, Prices Division Analytical Series, No. 10 (Ottawa: Statistics Canada), pp. 45–52.

    • Search Google Scholar
    • Export Citation

  • Fenwick. D. A. Ball, M. Silver and P.H. Morgan. 2003. “Price Collection and Quality Assurance of Item Sampling in the Retail Price Index: How Can Scanner Data Help?”, in M. Shapiro and R. Feenstra (eds.): Scanner Data and Price Indexes, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press, 2003), pp. 67–87.

    • Search Google Scholar
    • Export Citation

  • Ferger, W.F. 1931. “The Nature and Use of the Harmonic Mean”, in Journal of the American Statistical Association, Vol. 26, pp. 36–40.

    • Search Google Scholar
    • Export Citation

  • Ferger, W.F. 1936. “Distinctive Concepts of Price and Purchasing Power Index Numbers”, in Journal of the American Statistical Association, Vol. 31, pp. 258–272.

    • Search Google Scholar
    • Export Citation

  • Ferrari, G. and M. Riani. 1998. “On Purchasing Power Parities Calculation at the Basic Heading Level”, in Statistica. Vol. LVIII, pp. 91–108.

    • Search Google Scholar
    • Export Citation

  • Ferrari, G. and M. Riani. G. Gozzi and M. Riani. 1996. “Comparing GEKS and EPD Approaches for Calculating PPPs at the Basic Heading level”, in Eurostat: Improving the Quality of Price Indices: CPI and PPP (Luxembourg).

    • Search Google Scholar
    • Export Citation

  • Fisher, F.M. and K. Shell. 1972. “The Pure Theory of the National Output Deflator”, in The Economic Theory of Price Indexes (New York: Academic Press), pp. 49–113.

    • Search Google Scholar
    • Export Citation

  • Fisher, I. 1897. “The Role of Capital in Economic Theory”, in Economic Journal, Vol. 7, pp. 511–537.

  • Fisher, I. 1911. The Purchasing Power of Money (London: Macmillan).

  • Fisher, I. 1921, “The Best Form of Index Number”, in Journal of the American Statistical Association, Vol. 17, pp. 533–537.

  • Fisher, I. 1922. The Making of Index Numbers (Boston, MA: Houghton-Mifflin).

  • Fisher, W.C. 1913. “The Tabular Standard in Massachusetts History”, in Quarterly Journal of Economics, Vol. 27, pp. 417–451.

  • Fixler, D. and K.D. Zieschang. 1992. “Incorporating Ancillary Measures of Processes and Quality Change into a Superlative Productivity Index”, in Journal of Productivity Analysis, Vol. 2, pp. 245–267.

    • Search Google Scholar
    • Export Citation

  • Fixler, D. and K.D. Zieschang. and K.D. Zieshang. 2001. Price Indices for Financial Services, Paper presented at the Sixth Meeting of the International Working Group on Price Indices, Canberra, Apr. 2–6. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Flux, A.W. 1921. “The Measurement of Price Change”, in Journal of the Royal Statistical Society, Vol. 84, pp. 167–199.

  • Forsyth, F.G., and R.F. Fowler. 1981. “The Theory and Practice of Chain Price Index Numbers”, in Journal of the Royal Statistical Society A, Vol. 144, No. 2, pp. 224–247.

    • Search Google Scholar
    • Export Citation

  • Frisch, R. 1930. “Necessary and Sufficient Conditions Regarding the Form of an Index Number Which Shall Meet Certain of Fisher’s Tests”, in Journal of the American Statistical Association, Vol. 25, pp. 397–406.

    • Search Google Scholar
    • Export Citation

  • Frisch, R. 1936. “Annual Survey of General Economic Theory: The Problem of Index Numbers”, in Econometrica, Vol. 4, pp. 1–38.

  • Frost, S. 2001. The Construction of Price Indices for Deposit and Loan Facilities, Paper presented at the Sixth Meeting of the International Working Group on Price Indices, Canberra, Apr. 2–6. Available at: www.ottawagroup.org/.

    • Search Google Scholar
    • Export Citation

  • Funke, H. and J. Voeller. 1978. “A Note on the Characterization of Fisher’s Ideal Index”, in W. Eichhorn, R. Henn, O. Opitz and R.W. Shephard (eds.): Theory and Applications of Economic Indices (Würzburg: Physica-Verlag), pp. 177–181.

    • Search Google Scholar
    • Export Citation

  • Funke, H. and J. Voeller. G. Hacker and J. Voeller. 1979. “Fisher’s Circular Test Reconsidered”, in Schweizerische Zeitschrift für Volkswirtshaft und Statistik, Vol. 115, pp. 677–687.

    • Search Google Scholar
    • Export Citation

  • Garcke, E. and J.M. Fells. 1893. Factory Accounts: Their Principles and Practice, Fourth Edition (First Edition 1887) (London: Crosby, Lockwood and Son).

    • Search Google Scholar
    • Export Citation

  • Geary, R.C. 1958. “A note on the comparison of exchange rates and purchasing power between countries”, in Journal of the Royal Statistical Society (Series A), Vol. 121, pp. 97–99.

    • Search Google Scholar
    • Export Citation

  • Genereux, P.A. 1983. “Impact of the Choice of Formulae on the Canadian Consumer Price Index” in W.E. Diewert and C. Montmarquette (eds.): Price Level Measurement (Ottawa: Statistics Canada), pp. 489–535.

    • Search Google Scholar
    • Export Citation

  • Gilman, S. 1939. Accounting Concepts of Profit (New York: The Rolland Press Co.).

  • Goldberger, A.A. 1968. “The Interpretation and Estimation of Cobb-Douglas Functions”, in Econometrica, Vol. 35, pp. 464–472.

  • Goodhart, C. 2001. “What Weights should be Given to Asset Prices in the Measurement of Inflation?”, in Economic Journal, Vol. 111, June, F335 -F356.

    • Search Google Scholar
    • Export Citation

  • Gordon, R.J. 1990. The Measurement of Durable Goods Prices (Chicago, IL: University of Chicago Press).

  • Gordon, R.J. and Z. Griliches. 1997. “Quality Change and New Products”, in American Economic Review: Papers and Proceedings of the Hundred and Fourth Annual Meeting of the American Economic Association, Vol. 87, No. 2, pp. 84–88.

    • Search Google Scholar
    • Export Citation

  • Gorman, W.M. 1980. “A Possible Procedure for Analyzing Quality Differentials in the Egg Market”, in Review of Economic Studies, Vol. 47, pp. 843–856.

    • Search Google Scholar
    • Export Citation

  • Greenlees, J. 1997. “Expenditure Weight Updates and Measured Inflation”, Paper presented at the Third Meeting of the International Working Group on Price Indices, Voorburg, Apr. 16–18.

    • Search Google Scholar
    • Export Citation

  • Greenlees, J. 1999. Random Errors and Superlative Indexes, Paper presented at the Annual Conference of the Western Economic Association, 8 July, San Diego, CA.

    • Search Google Scholar
    • Export Citation

  • Greenlees, J. 2000. “Consumer Price Indexes: Methods for Quality and Variety Change”, in Statistical Journal of the United Nations Economic Commission for Europe, Vol. 17, No. 1, pp. 37–58.

    • Search Google Scholar
    • Export Citation

  • Greenlees, J. 2003, Introducing the Chained Consumer Price Index, Paper presented at the Seventh Meeting of the International Working Group on Price Indices, Paris, May 27–29. Available at: http://www.insee.fr.

    • Search Google Scholar
    • Export Citation

  • Griliches, Z. 1988. Technology, Education and Productivity: Early Papers with Notes to Subsequent Literature (New York: Basil Blackwell).

    • Search Google Scholar
    • Export Citation

  • Griliches, Z. 1990. “Hedonic Price Indices and the Measurement of Capital and Productivity: Some Historical Reflections”, in E.R. Berndt and J.E. Triplett (eds.): Fifty Years of Economic Measurement: The Jubilee of the Conference on Research in Income and Wealth, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 185–206.

    • Search Google Scholar
    • Export Citation

  • Gudnason. 1999. Use of Cash Register Data, Paper presented at the Fifth Meeting of the International Working Group on Price Indices, Reykjavik, Aug. 25–27. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Gudnason, R. 2003. How do we Measure Inflation? Some Measurement Problems, Paper presented at the Seventh Meeting of the International Working Group on Price Indices, May 27–29, Paris. Available at: http://www.insee.fr.

    • Search Google Scholar
    • Export Citation

  • Hardy, G.H., J.E. Littlewood and G. Pólya. 1934. Inequalities (Cambridge: Cambridge University Press).

  • Harper, M.J., E.R. Berndt and D.O. Wood. 1989. “Rates of Return and Capital Aggregation Using Alternative Rental Prices”, in D.W. Jorgenson and R. Landau (eds.): Technology and Capital Formation (Cambridge, MA: The MIT Press), pp. 331–372.

    • Search Google Scholar
    • Export Citation

  • Haschka, P. 2003. Simple Methods of Explicit QA for Services in Complex Pricing Schemes, Paper presented at the Seventh Meeting of the International Working Group on Price Indices, May 27–29, Paris. Available at: http://www.insee.fr.

    • Search Google Scholar
    • Export Citation

  • Hausman, J. A. 1997. “Valuation of New Goods Under Perfect and Imperfect Conditions”, in T.F. Bresnahan and R.J. Gordon (eds.): The Economics of New Goods, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 209–237.

    • Search Google Scholar
    • Export Citation

  • Hausman, J. A. 1999. “Cellular Telephone, New Products, and the CPI”, in Journal of Business and Economic Statistics, Vol. 17, No. 2, pp. 188–194.

    • Search Google Scholar
    • Export Citation

  • Hausman, J. A. 2002. Sources of Bias and Solutions to Bias in the CPI, NBER Working Paper 9298 (Cambridge, MA: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation

  • Hawkes, W.J. 1997. Reconciliation of Consumer Price Index Trends in Average Prices for Quasi-Homogeneous Goods Using Scanning Data, Paper presented at the Third Meeting of the International Working Group on Price Indices, Voorburg, Apr. 16–18. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Hawkes, W.J. and F.W, Piotrowski. 2003. “Using Scanner Data to Improve the Quality of Measurement in the Consumer Price Index”, in R.C. Feenstra and M.D. Shapiro (eds.): Scanner Data and Price Indexes, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 17–38.

    • Search Google Scholar
    • Export Citation

  • Haworth, M.F., D. Fenwick and R. Beaven. 1997. Recent Developments in the UK Retail Prices Index: Quality Management, Paper presented at the Third Meeting of the International Working Group on Price Indices, Voorburg, Apr. 16–18. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Hicks, J.R. 1940, “The Valuation of the Social Income”, in Economica, Vol. 7, pp. 105–124.

  • Hicks, J.R. 1941–42. “Consumers’ Surplus and Index Numbers”, in The Review of Economic Studies, Vol. 9, pp. 126–137.

  • Hicks, J.R. 1946. Value and Capital, Second Edition (Oxford: Clarendon Press).

  • Hidiroglou M.A. and J. M. Berthelot. 1986. “Statistical editing and imputation for periodic business surveys”, in Survey Methodology, Vol. 12, No. 1, pp. 73–83.

    • Search Google Scholar
    • Export Citation

  • Hill, R.J. 1995. Purchasing Power Methods of Making International Comparisons, Ph.D. Dissertation (Vancouver: University of British Columbia).

    • Search Google Scholar
    • Export Citation

  • Hill, R.J. 1999a. “Comparing Price Levels across Countries Using Minimum Spanning Trees”, in The Review of Economics and Statistics, Vol. 81, pp. 135–142.

    • Search Google Scholar
    • Export Citation

  • Hill, R.J. 1999b. “International Comparisons using Spanning Trees”, in A. Heston and R.E. Lipsey (eds.): International and Interarea Comparisons of Income, Output and Prices, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 109–120.

    • Search Google Scholar
    • Export Citation

  • Hill, R.J. 1999c. “Chained PPPs and Minimum Spanning Trees”, in A. Heston and R.E. Lipsey (eds.): International and Interarea Comparisons of Income. Output and Prices, NBER Studies in Income and Wealth (Chicago, IL: Chicago University Press), pp. 327–364.

    • Search Google Scholar
    • Export Citation

  • Hill, R.J. 1999d. “Comparing Price Levels Across Countries Using Minimum Spanning Trees”, in The Review of Economics and Statistics, Vol. 81, pp. 135–142.

    • Search Google Scholar
    • Export Citation

  • Hill, R.J. 2001. “Measuring Inflation and Growth Using Spanning Trees”, in International Economic Review, Vol. 42, pp. 167–185.

  • Hill, R.J. 2002. Superlative Index Numbers: Not All of them Are Super, Discussion Paper No. 2002/04, School of Economics (Sydney: University of New South Wales).

    • Search Google Scholar
    • Export Citation

  • Hill, T.P. 1988. “Recent Developments in Index Number Theory and Practice”, in OECD Economic Studies, Vol. 10, p. 123–148.

  • Hill, T.P. 1993. “Price and Volume Measures”, in System of National Accounts 1993 (Brussels/Luxembourg, New York, Paris, New York, and Washington, D.C.: Commission of the European Communities, IMF, OECD, World Bank and United Nations), pp. 379–406.

    • Search Google Scholar
    • Export Citation

  • Hill, T.P. 1996. Inflation Accounting: A Manual on National Accounting under Conditions of High Inflation (OECD: Paris).

  • Hill, T.P. 1998. “The Measurement of Inflation and Changes in the Cost of Living”, in Statistical Journal of the United Nations ECE, Vol. 15, pp. 37–51.

    • Search Google Scholar
    • Export Citation

  • Hill, T.P. 1999. COL Indexes and Inflation Indexes, Paper tabled at the Fifth Meeting of the International Working Group on Price Indices, Reykjavik, Aug. 25–27. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Hillinger, C. 2002. A General Theory of Price and Quantity Aggregation and Welfare Measurement, CISifo Working Paper No. 818 (Munich: University of Munich).

    • Search Google Scholar
    • Export Citation

  • Hoffmann, J. 1998. Problems of Inflation Measurement in Germany, Discussion Paper 1/98, Economic Research Group of the Deutsche Bundesbank (Frankfurt: Deutsche Bundesbank).

    • Search Google Scholar
    • Export Citation

  • Hoffmann, J. 1999. The Treatment of Quality Changes in the German Consumer Price Index, Paper presented at the Fifth Meeting of the International Working Group on Price Indices, Reykjavik, Aug. 25–27. Available at: http://www.ott.awa-group.org.

    • Search Google Scholar
    • Export Citation

  • Hoffmann, J. and C. Kurz. 2002. Rent Indices for Housing in West Germany: 1985 to 1998, Discussion Paper 01/02, Economic Research Centre of the Deutsche Bundesbank (Frankfurt: Deutsche Bundesbank).

    • Search Google Scholar
    • Export Citation

  • Holdway, M. 1999. An Alternative Methodology: Valuing Quality Changes for Microprocessors in the PPI, Unpublished Paper (Washington. D.C.: Bureau of Labor Statistics).

    • Search Google Scholar
    • Export Citation

  • Hotelling, H. 1925. “A General Mathematical Theory of Depreciation”, in Journal of the American Statistical Association, Vol. 20, pp. 340–353.

    • Search Google Scholar
    • Export Citation

  • Houthakker, H.S. 1952. “Compensated Changes in Quantities and Qualities Consumed”, in Review of Economic Studies, Vol. 19, pp. 155–164.

    • Search Google Scholar
    • Export Citation

  • Hoven, L. 1999. Some Observations on Quality Adjustment in the Netherlands, Unpublished Paper, Department of Consumer Prices (Voorburg: Statistics Netherland).

    • Search Google Scholar
    • Export Citation

  • Hulten, C.R. 1973. “Divisia Index Numbers”, in Econometrica, Vol. 41, pp. 1017–1026.

  • Hulten, C.R.. 1990. “The Measurement of Capital”, in E.R. Berndt and J.E. Triplett (eds.): Fifty Years of Economic Measurement: The Jubilee of the Conference on Research in Income and Wealth, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 119–158.

    • Search Google Scholar
    • Export Citation

  • Hulten, C.R. 1996. “Capital and Wealth in the Revised SNA”, in J.W. Kendrick (ed.): The New System of National Accounts (New York: Kluwer Academic Publishers), pp. 149–181.

    • Search Google Scholar
    • Export Citation

  • Hulten, C.R. and F.C. Wykoff. 1981a. “The Estimation of Economic Depreciation using Vintage Asset Prices”, in Journal of Econometrics, Vol. 15, pp. 367–396.

    • Search Google Scholar
    • Export Citation

  • Hulten, C.R.. 1981b. “The Measurement of Economic Depreciation”, in C.R. Hulten (ed.): Depreciation, Inflation and the Taxation of Income from Capital (Washington, D.C.: The Urban Institute Press), pp. 81–125.

    • Search Google Scholar
    • Export Citation

  • Hulten, C.R.. 1996. “Issues in the Measurement of Economic Depreciation: Introductory Remarks”, in Economic Inquiry, Vol. 34, pp. 10–23.

    • Search Google Scholar
    • Export Citation

  • International Labour Organization (ILO). 1987. Report of the Fourteenth International Conference of Labour Statisticians (Geneva).

  • International Labour Organization (ILO). 1990. ISCO-88: International Standard Classification of Occupations (Geneva).

  • International Labour Organization (ILO). 1998. “Guidelines concerning dissemination practices for labour statistics”, in Report of the Sixteenth International Conference of Labour Statisticians (Geneva). Web address: http://www.ilo.org/public/english/bureau/stat/standardsy guidelines/index.htm).

    • Search Google Scholar
    • Export Citation

  • International Labour Organization (ILO). 2003. Report III to the Seventeenth International Conference of Labour Statisticians (Geneva).

  • ILO, IMF, OECD, Eurostat, UNECE and the World Bank. 2004. Producer Price Index Manual (Brussels/Luxembourg, Geneva, Washington, D.C, Geneva, Washington, D.C).

    • Search Google Scholar
    • Export Citation

  • International Monetary Fund (IMF). General Data Dissemination System (GDDS). Web address: http://dsbb.imf. org/Applications/web/gdds/gddshome/.

    • Search Google Scholar
    • Export Citation

  • International Monetary Fund (IMF). Special Data Dissemination Standard (SDDS). Web address: http://dsbb.imf.org/Applications/web/sddshome.

    • Search Google Scholar
    • Export Citation

  • International Monetary Fund (IMF). 1993. Balance of Payments Manual, Fifth Edition (Washington, D.C.).

  • International Monetary Fund (IMF). 2001. Government Financial Statistics Manual (Washington, D.C.).

  • Ioannidis, C. and M. Silver. 1999. “Estimating Hedonic Indices: An Application to UK Television Sets”, in Journal of Economics. Zeitschrift für Nationalökonomie, Vol. 69, No. 1, pp. 71–94.

    • Search Google Scholar
    • Export Citation

  • ISO 9000, Geneva, International Standards Organization. 1994. Web address: http://iso.ch.

  • ISO 9001. Geneva, International Standards Organization. 2000. Web address: http://iso.ch.

  • Jacobsen, J. 1997. Variance Estimation and Sample Allocation in the Finnish CPI, Memo written for Statistics Finland, Mar. 11.

  • Jensen, J.L.W.V. 1906. “Sur les functions convexes et les inegalités entre les valeurs moyennes”, in Acta Math., Vol. 8, pp. 94–96.

    • Search Google Scholar
    • Export Citation

  • Jevons, W.S. 1863. “A Serious Fall in the Price of Gold Ascertained and its Social Effects Set Forth”, reprinted in Investigations in Currency and Finance (London: Macmillan and Co., 1884), pp. 13–118.

    • Search Google Scholar
    • Export Citation

  • Jevons, W.S. 1865. “The Variation of Prices and the Value of the Currency since 1782”, in Journal of the Statistical Society of London, Vol. 28, pp. 294–320; reprinted in Investigations in Currency and Finance (London: Macmillan and Co., 1884), pp. 119–150.

    • Search Google Scholar
    • Export Citation

  • Jevons, W.S. 1884. “A Serious Fall in the Value of Gold Ascertained and its Social Effects Set Forth. 1863”, in Investigations in Currency and Finance (London: Macmillan and Co.), pp. 13–118.

    • Search Google Scholar
    • Export Citation

  • Jorgenson, D.W. 1989. “Capital as a Factor of Production”, in D.W. Jorgenson and R. Landau (eds.): Technology and Capital Formation (Cambridge, MA: The MIT Press), pp. 1–35.

    • Search Google Scholar
    • Export Citation

  • Jorgenson, D.W. 1996. “Empirical Studies of Depreciation”, in Economic Inquiry, Vol. 34, pp. 24–42.

  • Jorgenson, D.W. and Z. Griliches. 1967. “The Explanation of Productivity Change”, in Review of Economic Studies, Vol. 34, pp, 249–283.

    • Search Google Scholar
    • Export Citation

  • Katz, A.J. 1983. “Valuing the Services of Consumer Durables”, in The Review of Income and Wealth, Vol. 29, pp. 405–427.

  • Kennedy, P. 1998. A Guide to Econometrics (Oxford: Blackwell Publishers).

  • Kenny, P.B. 1995. Errors in the Retail Prices Index, Memo written for the UK Central Statistical Office/Office for National Statistics, 8 Mar.

    • Search Google Scholar
    • Export Citation

  • Keynes, J.M. 1930. A Treatise on Money in Two Volumes; I; The Pure Theory of Money (London: Macmillan).

  • Khamis, S.H. 1970. “Properties and Conditions for the Existence of a New Type if Index Numbers”, in Sankhya, Series B, Vol. 32, pp. 81–98.

    • Search Google Scholar
    • Export Citation

  • Khamis, S.H. 1972. “A New System of index Numbers for National and International Purposes”, in Journal of the Royal Statistical Society, Series A, Vol. 135, pp. 96–121.

    • Search Google Scholar
    • Export Citation

  • Khamis, S.H. 1984. “On Aggregation methods for International Comparisons”, in Review of Income and Wealth, Vol. 30, No. 2, pp. 185–205.

    • Search Google Scholar
    • Export Citation

  • Knibbs,Sir G.H. 1924. “The Nature of an Unequivocal Price Index and Quantity Index”, in Journal of the American Statistical Association, Vol. 19, pp. 42–60 and 196–205.

    • Search Google Scholar
    • Export Citation

  • Kokoski, M.F., K. Waehrer and P. Rozaklis. 2001. Using Hedonic Methods for Quality Adjustment in the CPI: The Consumer Audio Products Component, Working Paper No, 344 (Washington, DC: Bureau of Labor Statistics).

    • Search Google Scholar
    • Export Citation

  • Kokoski, M.F., K. Waehrer and P. Rozaklis. B.R. Moulton and K.D. Zieschang. 1999. “Interarea Price Comparisons for Heterogeneous Goods and Several Levels of Commodity Aggregation”, in A. Heston and R.E. Lipsey (eds.): International and Interarea Comparisons of Income, Output and Prices, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 123–166.

    • Search Google Scholar
    • Export Citation

  • Konüs, A.A. 1924. “The Problem of the True Index of the Cost of Living”, in The Economic Bulletin of the Institute of Economic Conjuncture (in Russian), No. 9–10, pp. 64–71; published in English in 1939 in Econometrica, Vol. 7, pp. 10–29.

    • Search Google Scholar
    • Export Citation

  • Konüs, A.A. and S.S. Byushgens. 1926. “K probleme pokupatelnoi cilideneg”, in Voprosi Konyunkturi, Vol. 2, pp. 151–172.

  • Koskimäki. T, and M. Ylä-Jarkko. 2003. Segmented Markets and CPI Elementary Classifications, Paper presented at the Seventh Meeting of the International Working Group on Price Indices, Paris, May 27–29. Available at: http://www.insee.fr/.

    • Search Google Scholar
    • Export Citation

  • Koskimäki. T, and M. Ylä-Jarkko. and Y. Vartia. 2001. Beyond Matched Pairs and Griliches Type Hedonic Methods for Controlling Quality Changes in CPI Subindices, Paper presented at the Sixth Meeting of the International Working Group on Price Indices, Canberra, Apr. 2–6. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Kotler, P. 1991. Marketing Management, Seventh Edition (Englewood Cliffs, NJ: Prentice Hall).

  • Kravis, I.B., A.W. Heston and R. Summers. 1982. World Product and Income: International Comparisons of Real Gross Domestic Product (Baltimore, MD: Johns Hopkins University Press).

    • Search Google Scholar
    • Export Citation

  • Krueger, A.B. and A. Siskind. 1998. “Using Survey Data to Assess Bias in the Consumer Price Index”, in Monthly Labor Review, Vol. 121, No. 4, pp. 24–33.

    • Search Google Scholar
    • Export Citation

  • Lancaster, K.J. 1966. “A New Approach to Consumer Theory”, in Journal of Political Economy, Vol. 74, No. 2, pp. 132–156.

  • Lancaster, K.J. 1971, Consumer Demand: A New Approach (New York: Columbia University Press).

  • Lane, W. 2001. Addressing the New Goods Problem in the Consumer Price Index, Paper presented at the Sixth Meeting of the International Working Group on Price Indices, Canberra, Apr. 2–6. Available at http://www.ottawa.org.

    • Search Google Scholar
    • Export Citation

  • Laspeyres, E. 1871. “Die Berechnung einer mittleren Waar-enpreissteigerung”, in Jahrbücher für Nationalökonomie und Statistik, Vol. 16, pp. 296–314.

    • Search Google Scholar
    • Export Citation

  • Lau, L.J. 1979. “On Exact Index Numbers”, in Review of Economics and Statistics, Vol. 61, pp. 73–82.

  • Leaver, S.G. and D. Swanson. 1992. “Estimating Variances for the U.S. Consumer Price Index for 1987–1991”, in American Statistical Association: Proceedings of the Survey Research Methods Section (Alexandria, VS), pp. 740–745.

    • Search Google Scholar
    • Export Citation

  • Leaver, S.G. and D. Swanson. and R. Valliant. 1995. “Statistical Problems in Estimating the U.S. Consumer Price Index”, in Cox et al. (eds.): Business Survey Methods (New York: Wiley).

    • Search Google Scholar
    • Export Citation

  • Lebow, D.E. and J.B. Rudd. 2003. “Measurement Error in the Consumer Price Index: Where Do We Stand?”, in Journal of Economic Literature, Vol. 41, pp. 159–201.

    • Search Google Scholar
    • Export Citation

  • Lebow, D.E. and J.B. Rudd. J.M. Roberts and D.J. Stockton. 1994. Monetary Policy and the ‘Price Level’, Unpublished Paper (Washington, D.C.: Board of Governors of the Federal Reserve System), July.

    • Search Google Scholar
    • Export Citation

  • Lehr, J. 1885. Beiträge zur Statistik der Preise (Frankfurt: J.D. Sauerlander).

  • Leontief, W. 1936. “Composite Commodities and the Problem of Index Numbers”, in Econometrica, Vol. 4, pp. 39–59.

  • Lequiller, F. 1997. “Does the French Consumer Price Index Overstate Inflation?”, in L.M. Ducharme (ed.): Bias in the CPI: Experiences from Five OECD Countries, Prices Division Analytical Series, No. 10 (Ottawa: Statistics Canada), pp. 25–43.

    • Search Google Scholar
    • Export Citation

  • Levy, F., H. Beamish, R.J. Murnane and D. Aurtor. 1999. Computerization and Skills: Example from a Car Dealership, Brookings Program on Output and Productivity Measurement in the Services Sector, Workshop on Measuring the Output of Business Services, May 14, (Washington, D.C.: Brookings Institution).

    • Search Google Scholar
    • Export Citation

  • Ley, E. 2003. “Comment”, in R.C. Feenstra and M.D. Shapiro (eds.): Scanner Data and Price Indexes, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 379–382.

    • Search Google Scholar
    • Export Citation

  • Liegey .Jr, P.R. 1992. “Adjusting apparel indices in the CPI for quality differences”, in M.F. Foss, M. Manser and A. Young (eds.): Price Measurements and their Uses, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press).

    • Search Google Scholar
    • Export Citation

  • Liegey .Jr, P.R. 1994. “Apparel Price Indexes: Effects of Hedonic Adjustments”, in Monthly Labor Review, Vol. 117, pp. 38–45.

  • Liegey .Jr, P.R. 2000. Hedonic Quality Adjustment Methods for Microwave Ovens in the U.S. CPI, Methodology Paper (Washington, D.C.: Bureau of Labor Statistics).

    • Search Google Scholar
    • Export Citation

  • Linder, F. 1996. Reducing bias in the estimation of consumer price indices by using integrated data, Research Report (Voorburg: Statistics Netherlands).

    • Search Google Scholar
    • Export Citation

  • Lloyd. P.J. 1975. “Substitution Effects and Biases in Nontrue Price Indices”, in American Economic Review, Vol. 65, pp. 301–313.

  • Lowe, J. 1823. The Present State of England in Regard to Agriculture, Trade and Finance, Second Edition (London: Longman, Hurst, Rees, Orme and Brown).

    • Search Google Scholar
    • Export Citation

  • Lowe, R. 1996. “The Type and Extent of Quality Changes in the Canadian CPI”, in J. Dalen (ed.): Proceedings of the Second Meeting of the International Working Group on Price Indices (Stockholm: Statistics Sweden), pp. 231–249. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Lowe, R. 1999. The Use of the Regression Approach to Quality Change for Durables in Canada, Paper presented at the Fifth Meeting of the International Working Group on Price Indices, Reykjavik, Aug. 25–27. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Maddala, G.S. 1988. Introduction to Econometrics (New York: Macmillan).

  • Malmquist, S. 1953. “Index Numbers and Indifference Surfaces”, in Trabajos de Estadistica, Vol. 4, pp. 209–242.

  • Malpezzi, S., L. Ozanne and T. Thibodeau. 1987. “Micro-economic Estimates of Housing Depreciation”, in Land Economics, Vol. 63, pp. 372–385.

    • Search Google Scholar
    • Export Citation

  • Manser, M.E. and R.J. McDonald. 1988. “An Analysis of Substitution Bias in Measuring Inflation, 1959–85”, in Econometrics, Vol. 56, No. 4, pp. 909–930.

    • Search Google Scholar
    • Export Citation

  • Marshall, A. 1887. “Remedies for Fluctuations of General Prices”, in Contemporary Review, Vol. 51, pp. 355–375.

  • Marshall, A.. 1898. Principles of Economics, Fourth Edition (London: The Macmillan Co.).

  • Matheson, E. 1910. The Depreciation of Factories and their Valuation, Fourth Edition (London: E. & F.N. Spon).

  • McClelland, R. and M. Reinsdorf. 1999. Small Sample Bias in Geometric Mean and Seasoned CPI Component Indexes, Economic Working Paper (Washington, D.C.: Bureau of Labor Statistics).

    • Search Google Scholar
    • Export Citation

  • McCracken, P.M., J. Tobin et al. 1999. Measuring Prices in A Dynamic Economy: Re-Examining the CPI (New York: The Conference Board).

  • Mendelsohn, R. 1984. “Estimating the Structural Equations of Implicit Market and Household Production Functions”, in Review of Economics and Statistics, Vol. 66, No. 4, pp. 673–677.

    • Search Google Scholar
    • Export Citation

  • Mendershausen, H. 1937. “Annual Survey of Statistical Technique: Methods of Computing and Eliminating Changing Seasonal Fluctuations”, in Econometrica, Vol. 5, pp. 234–262.

    • Search Google Scholar
    • Export Citation

  • Merkel, F.K. 2000. Addressing New Item Bias in the Producer Price Indexes: A PPI Quality Improvement Initiative, Unpublished Paper (Washington, D.C.: Bureau of Labor Statistics).

    • Search Google Scholar
    • Export Citation

  • Mitchell, W.C. 1927. Business Cycles (New York: National Bureau of Economic Research).

  • Moulton, B.R. 1996a. Constant Elasticity Cost-of-Living Index in Share Relative Form (Washington, D.C.: Bureau of Labor Statistics), Dec.

    • Search Google Scholar
    • Export Citation

  • Moulton, B.R. 1996b. “Bias in the Consumer Price Index: What is the Evidence?”, in Journal of Economic Perspectives, Vol. 10, No. 4, pp. 159–177.

    • Search Google Scholar
    • Export Citation

  • Moulton, B.R. 2001, “The Expanding Role of Hedonic Methods in the Official Statistics of the United States”, in Proceedings of a Symposium on Hedonic Methods (Wiesbaden: Deutches Bundesbank and German Federal Statistical Office), June.

    • Search Google Scholar
    • Export Citation

  • Moulton, B.R. and K.E. Moses. 1997. “Addressing the Quality Change Issue in the Consumer Price Index”, in Brooking Papers on Economic Activity, Vol. 1, pp. 305–366.

    • Search Google Scholar
    • Export Citation

  • Moulton, B.R. and K.E. Moses, and E.P. Seskin. 1999. “A Preview of the 1999 Comprehensive Revision of the National Income and Product Accounts”, in Survey of Current Business. Vol. 79, pp. 6–17.

    • Search Google Scholar
    • Export Citation

  • Moulton, B.R. and K.E. Moses. and E.P. Seskin. T. LaFleur and K.E. Moses. 1999, “Research on Improved Quality Adjustment in the CPI: The Case of Televisions”, in W. Lane (ed.): Proceedings of the Fourth Meeting of the International Working Group on Price Indices (Washington, D.C.: Bureau of Labor Statistics), pp. 77–99. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Mudgett, B.D. 1955. “The Measurement of Seasonal Movements in Price and Quantity Indexes”, in Journal of the American Statistical Association, Vol. 50, pp. 93–98.

    • Search Google Scholar
    • Export Citation

  • Muellbauer, J. 1974. “Household Production Theory, Quality, and the ‘Hedonic Technique’”, in The American Economic Review, Vol. 64, No. 6, pp. 977–994.

    • Search Google Scholar
    • Export Citation

  • Murray, J. and N. Sarantis. 1999. “Price-Quality Relationships and Hedonic Price Indexes for Cars in the United Kingdom”, in International Journal of the Economics of Business, Vol. 6, No. 1, pp. 1–23.

    • Search Google Scholar
    • Export Citation

  • Muth, R.F. 1966. “Household Production and Consumer Demand Functions”, in Econometrica, Vol. 34, pp. 699–708.

  • Nevo, A. 2001. New Products. Quality Changes, and Welfare Measures Computed from Estimated Demand Systems, NBER Working Paper #W8425 (Cambridge. MA: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation

  • Norberg, A. 1999. “Quality Adjustment: The Case of Clothing”, in M. Silver and D. Fenwick (eds.): Proceedings of the Measurement of Inflation Conference (Cardiff: Cardiff University). Available at: http://www.cardiff.ac.uk.

    • Search Google Scholar
    • Export Citation

  • Nordhaus, W.D. 1998. “Quality Change in Price Indexes”, in Journal of Economic Perspectives, Vol. 12, No. 1, pp. 59–68.

  • Obst, Ca.l. 2000. “A Review of Bias in the CPI”, in Statistical Journal of the United Nations ECE, Vol. 17, pp. 37–58.

  • Office for National Statistics (UK). 1998. The Retail Prices Index: A Technical Manual. Available at: http://www.statistics.gov.uk.

  • Oi, W.Y. 1997. “The Welfare Implications of Invention”, in T.F. Bresnahan and R.J. Gordon (eds.): The Economics of New Goods, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 109–141.

    • Search Google Scholar
    • Export Citation

  • Okamoto. M. 1999. Empirical Study of Outlet Sampling Using Scanner Data, Paper presented at the ILO/ECE Joint Meeting on CPI. Geneva, Nov. 3–5. Available at: http://www.unece.org.

    • Search Google Scholar
    • Export Citation

  • Okamoto. M. 2001. Mid-Year Basket Index as a Practical Approximation to a Superlative Index, Paper presented at the Sixth Meeting of the International Working Group on Price Indices, Canberra, Apr. 2–6. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Opperdoes, E. 2001. Some Empirical Experiments with CES Functions, Unpublished Paper (Voorburg: Statistics Netherlands).

  • Organisation for Economic Co-operation and Development (OECD). 1997. Synthesis Paper on Shortcomings of the Consumer Price Index Measure of Inflation for Economic Policy Purposes, Paper prepared for Working Party No. 1 on Macroeconomic and Structural Policy Analysis, ECO/CPE/WP1(97)12, Sep. (Paris).

    • Search Google Scholar
    • Export Citation

  • Organisation for Economic Co-operation and Development (OECD). 1998. FISM, A Note by the OECD Secretariat, Prepared for the Joint OECD/ESCAP Meeting on National Accounts - 1993 System of National Accounts: Five Years On, Bangkok, May 4–8.

    • Search Google Scholar
    • Export Citation

  • Organisation for Economic Co-operation and Development (OECD). 1999. Purchasing Power Parities and Real Expenditures (Paris).

  • Organisation for Economic Co-operation and Development (OECD). 2001a. Measuring Productivity: Measurement of Aggregate and Industry-Level Productivity Growth (Paris).

    • Search Google Scholar
    • Export Citation

  • Organisation for Economic Co-operation and Development (OECD). 2001b. Measuring Capital: Measurement of Capital Stocks, Consumption of Fixed Capital and Capital Services (Paris).

    • Search Google Scholar
    • Export Citation

  • Osgood, W.F. 1925. Advanced Calculus (New York: Macmillan).

  • Paasche, H. 1874. “Uber die Preisentwicklung der letzten Jahre nach den Hamburger Borsennotirungen”, in Jahrbücher für Nationalökonomie und Statistik, Vol. 12, pp. 168–178.

    • Search Google Scholar
    • Export Citation

  • Pakes, A. 2001. A Reconsideration of Hedonic Price Indices with an Application to PC’s, Working Paper No. 8715 (Cambridge, MA: National Bureau of Economic Research), revised November 2001.

    • Search Google Scholar
    • Export Citation

  • Palgrave, R.H.I. 1886. “Currency and Standard of Value in England, France and India and the Rates of Exchange Between these Countries”, in Memorandum submitted to the Royal Commission on Depression of Trade and Industry, Third Report, Appendix B, pp. 312–390.

    • Search Google Scholar
    • Export Citation

  • Parker, P. 1992. “Price Elasticity Dynamics Over the Adoption Life Cycle”, in Journal of Marketing Research, Vol. XXIX, pp. 358–367.

    • Search Google Scholar
    • Export Citation

  • Pierson, N.G. 1895. “Index Numbers and Appreciation of Gold”, in Economic Journal, Vol. 5, pp. 329–335.

  • Pierson, N.G. 1896. “Further Considerations on Index-Numbers”, in Economic Journal, Vol. 6, pp. 127–131.

  • Pigou, A.C. 1920. The Economics of Welfare (London: Macmillan).

  • Pollak, R.A. 1975. “Subindexes of the Cost of Living”, in International Economic Review, Vol. 16, pp. 135–160.

  • Pollak, R.A. 1980. “Group Cost-of-Living Indexes”, in American Economic Review, Vol. 70, pp. 273–278.

  • Pollak, R.A. 1981. “The Social Cost-of-Living Index”, in Journal of Public Economics, Vol. 15, pp. 311–336.

  • Pollak, R.A. 1983. “The Theory of the Cost-of-Living Index”, in W.E. Diewert and C. Montmarquette (eds.): Price Level Measurement (Ottawa: Statistics Canada), pp. 87–161; reprinted in R.A. Pollak: The Theory of the Cost-of-Living Index (Oxford: Oxford University Press, 1989), pp. 3–52; also reprinted in W.E. Diewert (ed.): Price Level Measurement (Amsterdam: North-Holland, 1990), pp. 5–77.

    • Search Google Scholar
    • Export Citation

  • Pollak, R.A. 1989. “The Treatment of the Environment in the Cost-of-Living Index”, in R.A. Pollak: The Theory of the Cost-of-Living Index (Oxford: Oxford University Press), pp. 181–185.

    • Search Google Scholar
    • Export Citation

  • Pollak, R.A. 1998. “The Consumer Price Index: A Research Agenda and Three Proposals”, in Journal of Economic Perspectives, Vol. 12, No. 1, pp. 69–78.

    • Search Google Scholar
    • Export Citation

  • Popkin, J. 1997. “Improving the CPI: The Record and Suggested Next Steps”, in Business Economics, July, pp. 42–47.

  • Prais, S.J. 1959. “Whose Cost of Living?”, in The Review of Economic Studies, Vol. 26, pp. 126–134.

  • Prennushi, G. 2001. PPPs and Global Poverty: Strengths and Weaknesses, Paper presented at the Joint World Bank-OECD Seminar on Purchasing Power Parities: Recent Advances in Methods and Applications, Washington, D.C., Jan. 30–Feb. 2.

    • Search Google Scholar
    • Export Citation

  • Price Statistics Review Committee. 1961. The Price Statistics of the Federal Government (New York: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation

  • Rameshwar, S. 1998. “A Note on Weights for Consumer Price Indices”, in Inter-Stat No. 18 (Luxembourg, London, Paris: Eurostat, DfID, INSEE), pp. 89–96.

    • Search Google Scholar
    • Export Citation

  • Rao, D.S. Prasada. 1990. “A System of Log-Change Index Numbers for Multilateral Comparisons”, in J. Salazar-Carrillo and D.S. Prasada Rao (eds.): Comparisons of Prices and Real Products in Latin America (Amsterdam: North-Holland).

    • Search Google Scholar
    • Export Citation

  • Rao, D.S. Prasada. 1995. On the Equivalence of the Generalized Country-Product-Dummy (CPD) Method and the Rao-System for Multilateral Comparisons, Working Paper No. 5, Centre for International Comparisons (Philadelphia. PA: University of Pennsylvania).

    • Search Google Scholar
    • Export Citation

  • Rao, D.S. Prasada. 1997. “Aggregation Methods for International Comparison of Purchasing Power Parities and Real Income: Analytical Issues and Some Recent Developments”, in Proceedings of the International Statistical Institute, 51st Session, pp. 197–200.

    • Search Google Scholar
    • Export Citation

  • Rao, D.S. Prasada. 2001a. Integration of CPI and ICP: Methodological Issues, Feasibility and Recommendations, Paper presented at the Joint World Bank-OECD Seminar on Purchasing Power Parities: Recent Advances in Methods and Applications. Washington, D.C., Jan. 30–Feb. 2.

    • Search Google Scholar
    • Export Citation

  • Rao, D.S. Prasada. 2001b. Weighted EKS and Generalized Country Product Dummy Methods for Aggregation at Basic Heading Level and above Basic Heading Level. Paper presented at the Joint World Bank-OECD Seminar on Purchasing Power Parities: Recent Advances in Methods and Applications, Washington, D.C. Jan. 30–Feb. 2.

    • Search Google Scholar
    • Export Citation

  • Rao, D.S. Prasada. and K.S. Banerjee. 1984. “A Multilateral Index Number System Based on the Factorial Approach”, in Statistische Hefte, Vol. 27, pp. 297–313.

    • Search Google Scholar
    • Export Citation

  • Rao, D.S. Prasada. and M. Timmer. 2000. Multilateralisation of Manufacturing Sector comparisons: Issues, Methods and Empirical Results, Research Memorandum No. GD 47 (Groningen: Groningen Growth and Development Centre).

    • Search Google Scholar
    • Export Citation

  • Rao, D.S. Prasada. C.J. O’Donnell and E. Ball. 2000. Transitive Multilateral Comparisons of Agricultural Output and Productivity Using Minimum Spanning Trees and Generalized EKS Methods, Paper presented at the Workshop on Agricultural Productivity: Data, Methods, and Measures, March 9–10, Washington, D.C..

    • Search Google Scholar
    • Export Citation

  • Rasmussen, D.W. and T.W. Zuehlke. 1990. “On the Choice of Functional Form for Hedonic Price Functions”, in The Review of Economics and Statistics, Vol. 72, pp. 668–675.

    • Search Google Scholar
    • Export Citation

  • Reese, M. 2000. Hedonic Quality Adjustment Methods for College Textbooks for the U.S. CPI, Methodology paper (Cambridge, MA: Bureau of Labor Statistics). Available at: http://www.bls.gov.

    • Search Google Scholar
    • Export Citation

  • Reinsdorf, M.B. 1993. “The Effect of Outlet Price Differentials on the U.S. Consumer Price Index”, in M.F. Foss, M.E. Manser and A.H. Young (eds.): Price Measurement and their Uses, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 227–254.

    • Search Google Scholar
    • Export Citation

  • Reinsdorf, M.B. 1994. Price Dispersion, Seller Substitution and the U.S. CPI, Working Paper 252 (Washington, D.C.: Bureau of Labor Statistics).

    • Search Google Scholar
    • Export Citation

  • Reinsdorf, M.B. 1996. Constructing Basic Component Indexes for the U.S. CPI from Scanner Data: A Test Using Data on Coffee, Working Paper 277 (Washington, D.C.: Bureau of Labor Statistics.).

    • Search Google Scholar
    • Export Citation

  • Reinsdorf, M.B. 1998. Divisia Indices and the Representative Consumer Problem, Paper presented at the Fourth Meeting of the International Working Group on Price Indices, Washington, D.C., Apr. 22–24. Available at: http://www.Ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Reinsdorf, M.B. 2003. Personal Communication, Sep. 9.

  • Reinsdorf, M.B.and B.R. Moulton. 1997. “The Construction of Basic Components of Cost-of-Living Indexes”, in T.F. Bresnahan and R.J. Gordon (eds.): The Economics of New Goods, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press).

    • Search Google Scholar
    • Export Citation

  • Reinsdorf, M.B. P. Liegey, and K. Stewart. 1996. New Ways of Handling Quality Change in the U.S. Consumer Price Index, Working Paper 276 (Washington, D.C.: Bureau of Labor Statistics).

    • Search Google Scholar
    • Export Citation

  • Reinsdorf, M.B. W.E. Diewert and C. Ehemann. 2002. “Additive Decompositions for the Fisher, Tornqvist and Geometric Mean Indexes”, in Journal of Economic and Social Measurement, Vol. 28, pp. 51–61.

    • Search Google Scholar
    • Export Citation

  • Richardson, D.H. 2003. “Scanner Indexes for the Consumer Price Index”, in R.C. Feenstra and M.D. Shapiro (eds.): Scanner Data and Price Indexes, NBER Studies in Income and Wealth (Chicago, IL: The University of Chicago Press), pp. 39–65.

    • Search Google Scholar
    • Export Citation

  • Rosén, B. 1997a. “Asymptotic Theory for Order Sampling”, in Journal of Statistical Planning and Inference, Vol. 62, pp. 135–158.

  • Rosén, B. 1997b. “On Sampling with Probability Proportional to Size”, in Journal of Statistical Planning and Inference, Vol. 62, pp. 159–191.

    • Search Google Scholar
    • Export Citation

  • Rosen, S. 1974. “Hedonic Prices and Implicit Markets: Product Differentiation and Pure Competition”, in Journal of Political Economy, Vol. 82, pp. 34–49.

    • Search Google Scholar
    • Export Citation

  • Rothwell, D.P. 1958. “Use of Varying Seasonal Weights in Price Index Construction”, in Journal of the American Statistical Association, Vol. 53, pp. 66–77.

    • Search Google Scholar
    • Export Citation

  • Ryten, J. 1998. The Evaluation of the International Comparison Project (ICP), (Washington, D.C.: IMF).

  • Samuelson, P.A. 1953. “Prices of Factors and Goods in General Equilibrium”, Review of Economic Studies, Vol. 21, pp. 1–20.

  • Samuelson, P.A. and S. Swamy. 1974. “Invariant Economic Index Numbers and Canonical Duality: Survey and Synthesis”, in American Economic Review, Vol. 64, pp. 566–593.

    • Search Google Scholar
    • Export Citation

  • Särndal, C. E., B. Swensson and J. Wretman. 1992. Model Assisted Survey Sampling (New York: Springer-Verlag).

  • Schlömilch, O. 1858. “Über Mittelgrössen versehiedetier Ordnungen”, in Zeitschrift für Mathematik und Physik, Vol. 3, pp. 308–310.

    • Search Google Scholar
    • Export Citation

  • Schultz, B.J. (Szulc). 1996. “Treatment of Changes in Product Quality in Consumer Price Indices”, in J. Dalén (ed.): Proceedings of the Second Meeting of the International Working Group on Price Indices (Stockholm: Statistics Sweden), pp. 209–229. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Schultz, B.J. (Szulc) 1999. “Effects of Using Various Macro-Index Formulae in Longitudinal Price and Comparisons: Empirical Studies”, in W. Lane (ed.): Proceedings of the Fourth Meeting of the International Working Group on Price Indices (Washington, D.C.: Bureau of Labor Statistics), pp. 236–249. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Schultze, C.L. and C. Mackie (eds.). 2002. At What Price? Conceptualizing and Measuring Cost-of-Living and Price Indices (Washington, D.C.: National Academy Press).

    • Search Google Scholar
    • Export Citation

  • Scrope, G.P. 1833. Principles of Political Economy (London: Longman, Rees, Orme, Brown, Green and Longman).

  • Sellwood, D. 2001. Improving Quality Adjustment in Practice, Paper presented at the Sixth Meeting of the International Working Group on Price Indices, Canberra, Apr. 2–6. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Selvanathan, E.A. and D.S. Prasada Rao. 1994. Index Numbers: A Stochastic Approach (Ann Arbor, MI: University of Michigan Press).

  • Shapiro, M.D. and D.W. Wilcox. 1997a. “Alternative Strategies for Aggregating Prices in the CPI”, in Federal Reserve Bank of St. Louis Review, Vol. 79, No. 3, pp. 113–125.

    • Search Google Scholar
    • Export Citation

  • Shapiro, M.D. and D.W. Wilcox. and D.W. Wilcox. 1997b. Mismeasurement in the Consumer Price Index: An Evaluation, Working Paper No. W5590 (Cambridge, MA: National Bureau of Economic Research). Available at: http://www.nbcr.org.

    • Search Google Scholar
    • Export Citation

  • Shephard, R.W. 1953. Cost and Production Functions (Princeton, NJ: Princeton University Press).

  • Shephard, R.W. 1970. Theory of Cost and Production Functions (Princeton, NJ: Princeton University Press).

  • Shepler, N. 2000. Developing a Hedonic Regression Model for Refrigerators in the U.S. CPI, Methodology paper (Washington, D.C.: Bureau of Labor Statistics). Web site: http://www.bls.gov/cpi/cpirfr.htm.

    • Search Google Scholar
    • Export Citation

  • Shiratsuka, S. 1999. “Measurement Errors in the Japanese Consumer Price Index”, in Monetary and Economic Studies, Vol. 17, No. 3, pp. 69–102.

    • Search Google Scholar
    • Export Citation

  • Sidgwick, H. 1883. The Principles of Political Economy (London: Macmillan).

  • Silver, M. 1995. “Elementary Aggregates, Micro-Indices and Scanner Data: Some Issues in the Compilation of Consumer Price Indices”, in Review of Income and Wealth, Vol. 41, pp. 427–438.

    • Search Google Scholar
    • Export Citation

  • Silver, M. 1999. “An Evaluation of the Use of Hedonic Regressions for Basic Components of Consumer Price Indices”, in Review of Income and Wealth, Vol. 45, No. 1, pp. 41–56.

    • Search Google Scholar
    • Export Citation

  • Silver, M. 2002. The Use of Weights in Hedonic Regressions: The Measurement of Quality Adjusted Price Changes, Unpublished Paper, Cardiff Business School (Cardiff: Cardiff University).

    • Search Google Scholar
    • Export Citation

  • Silver, M. and S. Heravi. 2001a. “Scanner Data and the Measurement of Inflation”, in The Economic Journal, 111 June, F384 -F405.

  • Silver, M. and S. Heravi. and S. Heravi. 2001b. Hedonic Price Indices and the Matched Models Approach, Unpublished Paper, Cardiff Business School (Cardiff: Cardiff University).

    • Search Google Scholar
    • Export Citation

  • Silver, M. and S. Heravi. and S. Heravi. and S. Heravi. 2002. Why the CPI Matched Models Method May Fail Us, Working Paper 144 (Frankfurt: European Central Bank).

    • Search Google Scholar
    • Export Citation

  • Silver, M. and S. Heravi.and S. Heravi.and S. Heravi.and S. Heravi. 2003. “The Measurement of Quality Adjusted Price Changes”, in R.C. Feenstra and M.D. Shapiro (eds.): Scanner Data and Price Indexes, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 277–316.

    • Search Google Scholar
    • Export Citation

  • Sitter, R.R. and R. Balshaw. 1998. Evaluation of Bias and Variance Estimation of the RPI, Confidential Report to the Office for National Statistics (UK) (British Columbia: Simon Fraser University).

    • Search Google Scholar
    • Export Citation

  • Solomons, D. 1961. “Economic and Accounting Concepts of Income”, in The Accounting Review, Vol. 36, pp. 374–383.

  • Solow, R.M. 1957. “Technical Change and the Aggregate Production Function”, in Review of Economics and Statistics, Vol. 39, pp. 312–320.

    • Search Google Scholar
    • Export Citation

  • Statistics Sweden. 2001. Swedish Consumer Price Index: A Handbook of Methods (Stockholm).

  • Stone, R. 1956. Quantity and Price Indexes in the National Accounts (Paris: OECD).

  • Summers, R. 1973. “International Price Comparisons Based Upon Incomplete Data”, in Review of Income and Wealth, Vol. 19, No. 1, pp. 1–16.

    • Search Google Scholar
    • Export Citation

  • Sundgren, B. 1993. “Statistical Metainformation Systems Pragmatics, Semantics”, Syntateties, in Statistical Journal of the United Nations Economic Commission for Europe, Vol. 10, No. 2, pp. 121–142.

    • Search Google Scholar
    • Export Citation

  • Szulc, B.J. (Schultz) 1964. “Index Numbers of Multilateral Regional Comparisons” (in Polish), in Przeglad Statysticzny. Vol. 3, pp. 239–254.

    • Search Google Scholar
    • Export Citation

  • Szulc, B.J. (Schultz) 1983. “Linking Price Index Numbers,” in W.E. Diewert and C. Montmarquette (eds.): Price Level Measurement (Ottawa: Statistics Canada), pp. 537–566.

    • Search Google Scholar
    • Export Citation

  • Szulc, B.J. (Schultz) 1987. “Price Indices below the Basic Aggregation Level”, in Bulletin of Labour Statistics, Vol. 2, pp. 9–16.

    • Search Google Scholar
    • Export Citation

  • Tauchen, H. and A.D. Witte. 2001. Estimating Hedonic Models; Implications of the Theory, Technical Working Paper No. 271 (Cambridge, MA: National Bureau of Economic Research). Available at: http://www.nber.org.

    • Search Google Scholar
    • Export Citation

  • Teekens, R. and J. Koerts. 1972. “Some Statistical Implications of the Log Transformations of Multiplicative Models”, in Econometrica. Vol. 40, No. 5, pp. 793–819.

    • Search Google Scholar
    • Export Citation

  • Tellis, G.J. 1988. “The Price Elasticity of Selective Demand: A Meta-Analysis of Econometric Models of Sales”, in Journal of Marketing Research, Vol. 25, pp. 167–177.

    • Search Google Scholar
    • Export Citation

  • Theil, H. 1954. Linear Aggregation of Economic Relations (Amsterdam: North-Holland).

  • Theil, H. 1967, Economics and Information Theory (Amsterdam: North-Holland).

  • Törnqvist, L. 1936. “The Bank of Finland’s Consumption Price Index”, in Bank of Finland Monthly Bulletin, Vol. 10, pp. 1–8.

  • Törnqvist, L. and E. Törnqvist. 1937. “Vilket är förhällandet mellan finska markens och svenska kronans köpkraft?”, in Eko-nomiska Samfundets Tidskrift, Vol. 39, pp. 1–39; reprinted in Collected Scientific Papers of Leo Törnqvist (Helsinki: The Research Institute of the Finnish Economy. 1981), pp. 121–160.

    • Search Google Scholar
    • Export Citation

  • Trajtenberg, M. 1989. Economic Analysis of Product Innovation: The Case of CT Scanners, (Cambridge, MA: Harvard University Press).

  • Triplett, J.E. 1981. “Reconciling the CPI and the PCE Deflator”, in Monthly Labor Review, Sep., pp. 3–15.

  • Triplett, J.E. 1983. “Concepts of Quality in Input and Output Price Measures: A Resolution of the User-Value Resource-Cost Debate”, in M.F. Foss (ed.): The U.S. National Income and Product Accounts: Selected Topics, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 269–311.

    • Search Google Scholar
    • Export Citation

  • Triplett, J.E. 1987. “Hedonic Functions and Hedonic Indices”, in J. Eatwell, M. Milgate and P. Newman (eds.): The New Palgrave: A Dictionary of Economics, Vol, 2 (London: Macmillan), pp. 630–634.

    • Search Google Scholar
    • Export Citation

  • Triplett, J.E. 1990. “Hedonic Methods in Statistical Agency Environments: An Intellectual Biopsy”, in E.R. Berndt and J.E. Triplett (eds.): Fifty Years of Economic Measurement: The Jubilee of the Conference on Research in Income and Wealth, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 207–238.

    • Search Google Scholar
    • Export Citation

  • Triplett, J.E. 1997. “Current Status of the Debate on the Consumer Price Index in the U.S.”, in L.M. Ducharme (ed.): Bias in the CPI: Experiences from Five OECD Countries, Prices Division Analytical Series, No. 10 (Ottawa: Statistics Canada), pp. 53–60.

    • Search Google Scholar
    • Export Citation

  • Triplett, J.E. 1999, “The Solow Productivity Paradox: What do Computers do to Productivity?”, in Canadian Journal of Economics, Vol. 32, No. 2, Apr., pp. 309–334.

    • Search Google Scholar
    • Export Citation

  • Triplett, J.E. 2001. “Should the Cost-of-Living Index Provide the Conceptual Framework for a Consumer Price Index?”, in The Economic Journal, Vol. 111, June, F311 -F334.

    • Search Google Scholar
    • Export Citation

  • Triplett, J.E. 2002. Handbook on Quality Adjustment of Price Indexes for Information and Communication Technology Products, Draft, OECD Directorate for Science, Technology and Industry (Paris: OECD).

    • Search Google Scholar
    • Export Citation

  • Triplett, J.E. 2003. “Using Scanner Data in Consumer Price Indexes: Some Neglected Conceptual Considerations”, in R.C. Feenstra and M.D. Shapiro (eds.): Scanner Data and Price Indexes, NBER Studies in Income and Wealth (Chicago, IL: University of Chicago Press), pp. 151–162.

    • Search Google Scholar
    • Export Citation

  • Trivedi, P.K. 1981. “Some Discrete Approximations to Divisia Integral Indices”, in International Economic Review, Vol. 22, pp. 71–77.

    • Search Google Scholar
    • Export Citation

  • Turvey, R. 1979. “The Treatment of Seasonal Items in Consumer Price Indices”, in Bulletin of Labour Statistics, Fourth Quarter (Geneva: ILO), pp. 13–33.

    • Search Google Scholar
    • Export Citation

  • Turvey, R. 1996, Elementary Aggregate (micro) Indexes, Paper presented at the Eurostat Seminar on Improving the Quality of Price Indices: CPI and PPP, Florence, Dec. 18–20, 1995.

    • Search Google Scholar
    • Export Citation

  • Turvey, R. 1998. “New Outlets and New Products”, in B. Balk (ed.): Proceedings of the Third Meeting of the International Working Group on Price Indices (Voorburg: Statistics Netherlands), pp. 97–110.

    • Search Google Scholar
    • Export Citation

  • Turvey, R. 1999. “Incorporating New Models into a CPI: PCs as an Example”, in M. Silver and D. Fenwick (eds.): Proceedings of the Measurement of Inflation Conference (Luxembourg, London, Cardiff: Eurostat, Office for National Statistics, Cardiff University). Available at: http://www.cardiff.ac.uk.

    • Search Google Scholar
    • Export Citation

  • Turvey, R. 2000. “True Cost of Living Indexes”, in R. Gudnason and D. Gylfadottir (eds.): Proceedings of the Fifth Meeting of the International Working Group on Price Indices (Reykjavik: Statistics Iceland). Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Turvey, R. et al. 1989. Consumer Price Indices: An ILO Manual (Geneva: ILO).

  • U.S. Bureau of Labor Statistics. 1983. “Changing the Home Ownership Component Of the Consumer Price Index to Rental Equivalence”, in CPI Detailed Report (Washington, D.C.).

    • Search Google Scholar
    • Export Citation

  • U.S. Bureau of Labor Statistics. 1997. BLS Handbook of Methods, Bulletin 2490 (Washington, D.C.).

  • U.S. Bureau of Labor Statistics. 1998. “Measurement Issues in the Consumer Price Index”, in Statistical Journal of the United Nations ECE, Vol. 15, pp. 1–36.

    • Search Google Scholar
    • Export Citation

  • U.S. General Accounting Office. 2000. Consumer Price Index: Update of Bosk in Commission’s Estimate of Bias, Report GAO/GGD-00–50 (Washington, DC), Feb.

    • Search Google Scholar
    • Export Citation

  • U.S. Senate, Committee on Finance. 1996. Final Report of the Advisory Commission to Study the Consumer Price Index, Print 104–72, 104 Cong., 2nd Session (Washington, DC: Government Printing Office).

    • Search Google Scholar
    • Export Citation

  • United Nations. 1990. International Standard Industrial Classification of All Economic Activities, Statistical Papers Series M, No. 4, Rev. 3 (New York).

    • Search Google Scholar
    • Export Citation

  • United Nations. 1992. Handbook of the International Comparison Program, Series F, No. 62 (New York).

  • United Nations. 1994. Fundamental Principles of Official Statistics, Adopted by the UN Statistical Commission. UN Economic and Social Council, 1994, Report of the Special Session of the Statistical Commission, New York, 11–15 Apr., 1994, E/1994/29 (New York).

    • Search Google Scholar
    • Export Citation

  • United Nations. 1998a. Principles and Recommendations for Population and Housing Censuses. Revision 1. Statistical Papers Series M, No. 67/Rev. 1, Sales No. E.98.XVII.8 (New York).

    • Search Google Scholar
    • Export Citation

  • United Nations. 1998b. Central Product Classification. CPC. Version 1.0, Statistical Papers Series M, No. 77, Ver. 1.0 (New York).

  • United Nations. 1999. Classifications of Expenditure According to Purpose, Statistical Papers Series M, No. 84 (New York).

  • United Nations. 2002. International Standard Industrial Classification of All Economic Activities, ISIC, Revision 3.1 (New York: United Nations Statistical Division).

    • Search Google Scholar
    • Export Citation

  • Van Ijzeren, J. 1987. Bias in International Index Numbers: A Mathematical Elucidation, Dissertation for the Hungarian Academy of Sciences (The Hague: Koninklijke Bibliotheek).

    • Search Google Scholar
    • Export Citation

  • van Mulligen, P.H. 2003. Quality aspects in price indices and international comparisons: Applications of the hedonic method, Ph.D. thesis (Groningen: University of Groningen). Web site: http://www.cbs.nl/en/publications/articles/generat/theses/theses.htm.

    • Search Google Scholar
    • Export Citation

  • Vartia, Y.O. 1976. Relative Changes and Index Numbers (Helsinki: The Research Institute of the Finnish Economy).

  • Vartia, Y.O. 1978. “Fisher’s Five-Tined Fork and Other Quantum Theories of Index Numbers”, in W. Eichhorn, R. Henn, O. Opitz and R.W. Shephard (eds.): Theory and Applications of Economic Indices (Wurzburg: Physica-Verlag), pp. 271–295.

    • Search Google Scholar
    • Export Citation

  • Ville, J. 1946. “The Existence-Conditions of a Total Utility Function” (in French); translated in 1951 in The Review of Economic Studies, Vol. 19, pp. 123–128.

    • Search Google Scholar
    • Export Citation

  • Vogt, A. 1977. “Zum Indexproblem: Geometrische Darstellung sowie eine neue Formel”, in Schweizerische Zeitschrift für Volkswirtschaft und Statistik, Vol. 113, pp. 73–88.

    • Search Google Scholar
    • Export Citation

  • Vogt, A. 1978. “Divisia Indices on Different Paths”, in W. Eichhorn, R. Henn, O. Opitz and R.W. Shephard (eds.): Theory and Applications of Economic Indices (Wurzburg: Physica-Verlag), pp. 297–305.

    • Search Google Scholar
    • Export Citation

  • Vogt, A. 1980. “Der Zeit und der Faktorumkehrtest als ‘Finders of Tests’”, in Statistische Hefte, Vol. 21, pp. 66–71.

  • Vogt, A.and J. Barta. 1997. The Making of Tests for Index Numbers (Heidelberg: Physica-Verlag).

  • von Auer, L. 2001. An Axiomatic Checkup for Price Indices, Working Paper No. 1/2001, Faculty of Economics and Management (Magdeburg: Otto von Guericke University).

    • Search Google Scholar
    • Export Citation

  • von Auer, L. 2002. “Spurious Inflation: The Legacy of Laspeyres and Others”, in The Quarterly Review of Economics and Finance, Vol. 42, pp. 529–542.

    • Search Google Scholar
    • Export Citation

  • von der Lippe, P. 2001. Chain Indices: A Study in Price Index Theory, Publication Series Spectrum of Federal Statistics, Vol. 16 (Wiesbaden: Statistisches Bundesamt).

    • Search Google Scholar
    • Export Citation

  • Walras, L. 1954. Elements of Pure Economics, translated from French by W. Jaffe (London: George Allen and Unwin); first published in 1874.

    • Search Google Scholar
    • Export Citation

  • Walsh, C.M. 1901. The Measurement of General Exchange Value (New York: Macmillan and Co.).

  • Walsh, C.M. 1921a. The Problem of Estimation (London: P.S. King & Son).

  • Walsh, C.M. 1921b. “Discussion”, in Journal of the American Statistical Association, Vol. 17, pp. 537–544.

  • Walsh, C.M. 1932. “Index Numbers”, in E.R.A. Seligman (ed.): Encyclopedia of the Social Sciences, Vol. 7 (New York: The Macmillan Co.), pp. 652–658.

    • Search Google Scholar
    • Export Citation

  • Ward, M. 2001. True Comparisons in Real and Money Terms, Paper presented at the Joint World Bank-OECD Seminar on Purchasing Power Parities: Recent Advances in Methods and Applications, Washington, D.C., Jan. 30–Feb. 2.

    • Search Google Scholar
    • Export Citation

  • Westergaard, H. 1890. Die Grundzdge der Theorie der Statistik (Jena: Fischer).

  • White, A.G. 1999. “Measurement Biases in Consumer Price Indexes”, in International Statistical Review, Vol. 67, No. 3, pp. 301–325.

    • Search Google Scholar
    • Export Citation

  • White, A.G. 2000. “Outlet Types and the Canadian Consumer Price Index”, in Canadian Journal of Economics, Vol. 33, pp. 488–505.

  • Wold, H. 1944. “A Synthesis of Pure Demand Analysis, Part 3”, in Skandinavisk Aktuarietidskrift, Vol. 27, pp. 69–120.

  • Wold, H. 1953. Demand Analysis (New York: John Wiley).

  • Wooldridge, J.M. 1996. “Estimating Systems of Equations with Different Instruments for Different Equations”, in Journal of Econometrics, Vol. 74, pp. 387–405.

    • Search Google Scholar
    • Export Citation

  • Woolford, K. 1999. “Measuring Inflation: A Framework Based on Domestic Final Purchases”, in M. Silver and D. Fenwick: Proceedings of the Measurement of Inflation Conference (Cardiff: Cardiff University), pp. 534–543.

    • Search Google Scholar
    • Export Citation

  • Woolford, K. 2001. Financial Services in the Consumer Price Index, Paper presented at the Sixth Meeting of the International Working Group on Price Indices, Canberra, Apr. 2–6. Available at: http://www.ottawagroup.org.

    • Search Google Scholar
    • Export Citation

  • Wynne, M.A. 1997. “Commentary”, in Federal Reserve Bank of St. Louis Review, Vol. 79, No. 3, pp. 161–167.

  • Wynne, M.A. 1999. Core Inflation: A Review of Some Conceptual Issues, Research Department Working Paper 99–03 (Dallas, TX: Federal Reserve Bank of Dallas).

    • Search Google Scholar
    • Export Citation

  • Wynne, M.A. and F.D. Sigalla. 1994. “The Consumer Price Index”, in Federal Reserve Bank of Dallas Economic Review, Second Quarter, pp. 1–22.

    • Search Google Scholar
    • Export Citation

  • Young, A. 1812. An Inquiry into the Progressive Value of Money in England as Marked by the Price of Agricultural Products (Piccadilly: Hatchard).

    • Search Google Scholar
    • Export Citation

  • Yule, G.U. 1921. “Discussion of Mr. Flux’s Paper”, in Journal of the Royal Statistical Society, Vol. 84, pp. 199–202.

  • Zarnowitz, V. 1961. “Index Numbers and the Seasonality of Quantities and Prices”, in G.J. Stigler (Chair): The Price Statistics of the Federal Government (New York: National Bureau of Economic Research), pp. 233–304.

    • Search Google Scholar
    • Export Citation

  • Zieschang, K.D. 1988. The Characteristics Approach to the Problem of New and Disappearing Goods in Price Indexes. Working Paper No. 183 (Washington, D.C.: Bureau of Labor Statistics).

    • Search Google Scholar
    • Export Citation

  • Zieschang, K.D. P.A. Armnecht and D. Smith. 2001. Integrated Inter-Area and International Price Comparisons with Consumer Price Index Compilation, Paper presented at the Joint World Bank-OECD Seminar on Purchasing Power Parities: Recent Advances in Methods and Applications, Washington, D.C., Jan. 30–Feb. 2.

    • Search Google Scholar
    • Export Citation